TheVoice project - PhD Offers

TheVoice project (2017-2021) funded by the French Research National Agency (ANR) proposes two PhD thesis. TheVoice project aims to create voices for audiovisual production in the field of the creative, cultural, and entertainment industry. The scientific objective of the project is to study the voices of professional actors, naturally expressive, in order to create innovative voice design solutions. The consortium, composed of recognized laboratories and industrialists (Ircam, LIA, Dubbing Brothers), aims to consolidate a position of excellence for “Made-in-France” research and digital technologies, and to promote the French culture all over the the world.

Deep learning for voice recommendation

The objective of the thesis is to create a voice recommendation system based on deep neural networks, by exploiting the entire “vocal palette” of professional actors and integrating information related to acoustics, perception (what the listener perceives, without context), and reception (what the spectator perceives “in situation” in a movie depending on his social and cultural expectations).

Contacts: jean-francois.bonastre@univ-avignon.fr, Nicolas.Obin@ircam.fr

Expressive voice identity conversion

The objective of the thesis is to create a voice identity conversion system able to reproduce the voice of professional actors from naturally expressive and real acted conditions, by exploiting the audio tracks of movies, series, etc. The thesis will be based on the long-term experience in voice analysis and transformation and the existing voice conversion system developed at Ircam, currently used for professional productions.

Contact: Nicolas.Obin@ircam.fr

Candidates must have a master degree in computer science (or equivalent) with skills in audio signal processing, machine learning, and informatics (python, C++). A preliminary experience in speech processing would be greatly appreciated.

Applications (CV + motivation letters) must be sent before: 15/09/2017

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Applications are invited for a research position in text to speech systems at the Language and Voice Laboratory (lvl.ru.is) at Reykjavik University's School of Science and Engineering. The position is sponsored by the Icelandic Language Technology fund grant 'Environment for building text-to-speech synthesis for Icelandic.' The main aim of the work will be to set up and advance research on speech synthesis back-end architectures for parametric speech synthesis. The successful candidate will work closely with the other members of the lab who focus on the language specific problems such as text normalization, phonemic analysis and phrasing. Even though the main objective of the work will be on Icelandic, working with other languages will be welcome. The successful candidate will contribute to the academic output of the lab as well as the publication of an open TTS environment for Icelandic.
 
Skills and qualifications
        ? MSc/PhD degree in applied mathematic, statistics, computational engineering or computer science is preferable
        ? Knowledge of mathematical modeling is preferrable (e.g. differential equations, neural networks, linear systems)
        ? Good skills in applying and analysing algorithms
        ? Good knowledge of Linux is preferable
        ? Ability to use shell scripts is advantageous (bash, awk, sed)
        ? Good programming skills are necessary (e.g. C++, Java or Python)
 
Fixed-term
The funds for this post are available for 24 months in the first instance.
 
Further information regarding the position provides Jón Guðnason (jg@ru.is), associate professor at School of Science and Engineering, and Anna Björk Nikulásdóttir, research specialist at School of Science and Engineering. Interviews will start September 14th, but applications received after that date will be taken into consideration if the position has not been filled by December 1st 2017. Applications must be submitted on the Reykjavík University website, here below. All inquiries and applications are treated as confidential.

http://radningar.hr.is/storf/ViewJobOnWeb.aspx?jobid=3005

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Keywords: Natural language understanding, decision support system, smart
home

The Laboratoire d'Informatique de Grenoble (LIG) of the University
Grenoble Alpes, Grenoble, France invites applications for a PhD position
in Computational Linguistics for Ambient Intelligence.

University of Grenoble Alpes is situated in a high-tech city located at
the heart of the Alps, in outstanding scientific and natural
surroundings. It is 3h by train from Paris ; 2h from Geneva and is less
than 1h from Lyon international airport.

The position starts in September 2017 and ends in July 2020 and is
proposed in the context of the national project Vocadom
(http://vocadom.imag.fr/) whose aim is to build technologies that make
natural hand-free speech interaction with a home automation system
possible from anywhere in the home even in adverse conditions
[Vacher2015].

The aim of the PhD will be to build a new generation of situated spoken
human machine interaction where uttered sentences by a human are
understood within the context of the interaction in the home. The
targeted application is a distant speech hand free and ubiquitous voice
user interface to make the home automation system react to voice
commands [Chahuara2017]. The system should be able to process possibly
erroneous outputs from an ASR system (Automatic Speech Recognition) to
extract meaning related to a voice command and to decide about which
command to execute or to send a relevant feed-back to the user. The
challenge will be to constantly adapt the system to new lexical phrases
(no a priori grammar), new situations (e.g., unseen user, context) and
change in the house (e.g., new device, device out of order). In this
work, we propose to extend classical S/NLU (Natural Language
Understanding) approaches by including non-linguistic contextual
information in the NLU process to tackle the ambiguity and borrow
zero-shot learning techniques [Ferreira2015] to extend the lexical space
on-line. Reinforcement learning is targeted to adapt the models to the
user(s) all along the use of the system [Mnih2015].  The candidate will
be strongly encouraged to publish their progress to the main events of
the field (ACL, Interspeech, Ubicomp).  The PhD candidate will also be
involved in experiments including real smart-home and real users
(elderly people and people with visual impairment) [Vacher2015].

REFERENCES :
[Mnih2015] Mnih, Kavukcuoglu et al.  Human-level control through deep
reinforcement learning. Nature 518, 529?533

[Chahuara2017] Chahuara, F. Portet, M. Vacher Context-aware decision
making under uncertainty for voice-based control of smart home Expert
Systems with Applications, Elsevier, 2017, 75, pp.63-79.

[Ferreira2015] E Ferreira, B Jabaian, F Lefevre Online adaptative
zero-shot learning spoken language understanding using word-embedding
Acoustics, Speech and Signal Processing (ICASSP), 2015

[Vacher2015] M. Vacher, S. Caffiau, F. Portet, B. Meillon, C. Roux, E.
Elias, B. Lecouteux, P. Chahuara. Evaluation of a context-aware voice
interface for Ambient Assisted Living: qualitative user study vs.
quantitative system evaluation. ACM - Transactions on Speech and
Language Processing, Association for Computing Machinery, 2015,
pp.5:1-5:36.

JOB REQUIREMENTS AND QUALIFICATIONS

- Master?s degree in Computational Linguistics or Artificial
Intelligence (Computer Science can also be considered)
- Solid programming skills,
- Good background in machine learning,
- Excellent English communication and writing skills,
- Good command of French (mandatory),
- Experience in experimentation involving human participants would be a
   plus
- Experience in dialogue systems would be a plus plus

Applications should include:

- Cover letter outlining interest in the position
- Names of two referees
- Curriculum Vitae (CV) (with publications if applicable)
- Copy of the university marks (grade list)

and be sent to michel.vacher@imag.fr and francois.portet@imag.fr

Research Group Website : http://getalp.imag.fr
Research project website : http://vocadom.imag.fr/

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IRCAM ( www.ircam.fr ) and L2S at University Paris Saclay ( www.l2s.centralesupelec.fr ) are jointly offering two new PostDoc positions for our current international project Dig that Lick: Analyzing large-scale data for melodic patterns in jazz performances ( dig-that-lick.eecs.qmul.ac.uk ). The project gathers six different universities across four countries (USA, UK, Germany, France).

The planned dates for the project are: 1 Oct 2017 - 30 Sep 2019.

* About the 'Dig that Lick' project: *
The recorded legacy of jazz spans a century and provides a vast corpus of data documenting its development. Recent advances in digital signal processing and data analysis technologies enable automatic recognition of musical structures and their linkage through metadata to historical and social context. Automatic metadata extraction and aggregation give unprecedented access to large collections, fostering new interdisciplinary research opportunities. This project aims to develop innovative technological and music-analytical methods to gain fresh insight into jazz history by bringing together renowned scholars and results from several high-profile projects. Musicologists and computer scientists will together create a deeper and more comprehensive understanding of jazz in its social and cultural context. We exemplify our methods via a full cycle of analysis of melodic patterns, or licks, from audio recordings to an aesthetically contextualised and historically situated understanding.
More information can be found at: dig-that-lick.eecs.qmul.ac.uk


* Position description: *
Dig that Lick relies on audio music content analysis algorithms. IRCAM & L2S are looking for 2 Post-Doctoral Research assistants (starting Oct. 1st, 2017) for the development of MIR algorithms:
? one 24-month post-doctoral position to develop robust algorithms for automatic melody extraction (AME) from audio signals
? one 12-month post-doctoral position to develop robust algorithms for automatic analysis of harmonic and metrical structure from audio signals

* Required profiles: *
? High skills in audio signal processing and in machine learning (the candidate should preferably hold a PHD in one of these fields)
? High skills in Matlab and/or Python programming
? Good knowledge of Linux, Windows, Mac-OS environments
? High productivity, methodical works, ability to work independently and in a creative way, excellent programming style.
? Strong communication skills in English (French is not required)
? Interest/background in Jazz music will be appreciated

The hired researchers will collaborate with the development team and participate in the project activities (evaluation of technologies, meetings, specifications, reports). Strong interactions with teams from the other participating universities are expected.

* Application Procedure / More information: *
Applications must include a detailed CV with a list of publications and a motivation letter. Applications and any suitable information are to be emailed to: H. Papadopoulos [ircam.l2s.digthatlick@gmail.com] and G. Peeters [peeters at ircam dot fr]

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Applications are invited for a research position in text to speech systems at the Language and Voice Laboratory (lvl.ru.is) at Reykjavik University's School of Science and Engineering. The position is sponsored by the Icelandic Language Technology fund grant 'Environment for building text-to-speech synthesis for Icelandic.' The main aim of the work will be to set up and advance research on speech synthesis back-end architectures for parametric speech synthesis. The successful candidate will work closely with the other members of the lab who focus on the language specific problems such as text normalization, phonemic analysis and phrasing. Even though the main objective of the work will be on Icelandic, working with other languages will be welcome. The successful candidate will contribute to the academic output of the lab as well as the publication of an open TTS environment for Icelandic.
 
Skills and qualifications
        ? MSc/PhD degree in applied mathematic, statistics, computational engineering or computer science is preferable
        ? Knowledge of mathematical modeling is preferrable (e.g. differential equations, neural networks, linear systems)
        ? Good skills in applying and analysing algorithms
        ? Good knowledge of Linux is preferable
        ? Ability to use shell scripts is advantageous (bash, awk, sed)
        ? Good programming skills are necessary (e.g. C++, Java or Python)
 
Fixed-term
The funds for this post are available for 24 months in the first instance.
 
Further information regarding the position provides Jón Guðnason (jg@ru.is), associate professor at School of Science and Engineering, and Anna Björk Nikulásdóttir, research specialist at School of Science and Engineering. Interviews will start September 14th, but applications received after that date will be taken into consideration if the position has not been filled by December 1st 2017. Applications must be submitted on the Reykjavík University website, here below. All inquiries and applications are treated as confidential.

http://radningar.hr.is/storf/ViewJobOnWeb.aspx?jobid=3005

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2 Post-Doc/Research positions in Audio Music Content Analysis
Project: 'Dig that Lick: Analyzing large-scale data for melodic patterns in jazz performances'
Place: IRCAM & L2S, Paris, France
Duration: 2 years and 1 year
Start: October 1st, 2017
Salary: according to background and experience


Dear colleagues, dear friends,

IRCAM ( www.ircam.fr ) and L2S at University Paris Saclay ( www.l2s.centralesupelec.fr ) are jointly offering two new PostDoc positions for our current international project Dig that Lick: Analyzing large-scale data for melodic patterns in jazz performances ( dig-that-lick.eecs.qmul.ac.uk ). The project gathers six different universities across four countries (USA, UK, Germany, France).

The planned dates for the project are: 1 Oct 2017 - 30 Sep 2019.

* About the 'Dig that Lick' project: *
The recorded legacy of jazz spans a century and provides a vast corpus of data documenting its development. Recent advances in digital signal processing and data analysis technologies enable automatic recognition of musical structures and their linkage through metadata to historical and social context. Automatic metadata extraction and aggregation give unprecedented access to large collections, fostering new interdisciplinary research opportunities. This project aims to develop innovative technological and music-analytical methods to gain fresh insight into jazz history by bringing together renowned scholars and results from several high-profile projects. Musicologists and computer scientists will together create a deeper and more comprehensive understanding of jazz in its social and cultural context. We exemplify our methods via a full cycle of analysis of melodic patterns, or licks, from audio recordings to an aesthetically contextualised and historically situated understanding.
More information can be found at: dig-that-lick.eecs.qmul.ac.uk


* Position description: *
Dig that Lick relies on audio music content analysis algorithms. IRCAM & L2S are looking for 2 Post-Doctoral Research assistants (starting Oct. 1st, 2017) for the development of MIR algorithms:
? one 24-month post-doctoral position to develop robust algorithms for automatic melody extraction (AME) from audio signals
? one 12-month post-doctoral position to develop robust algorithms for automatic analysis of harmonic and metrical structure from audio signals

* Required profiles: *
? High skills in audio signal processing and in machine learning (the candidate should preferably hold a PHD in one of these fields)
? High skills in Matlab and/or Python programming
? Good knowledge of Linux, Windows, Mac-OS environments
? High productivity, methodical works, ability to work independently and in a creative way, excellent programming style.
? Strong communication skills in English (French is not required)
? Interest/background in Jazz music will be appreciated

The hired researchers will collaborate with the development team and participate in the project activities (evaluation of technologies, meetings, specifications, reports). Strong interactions with teams from the other participating universities are expected.

* Application Procedure / More information: *
Applications must include a detailed CV with a list of publications and a motivation letter. Applications and any suitable information are to be emailed to: H. Papadopoulos [ircam.l2s.digthatlick@gmail.com] and G. Peeters [peeters at ircam dot fr]

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      Research Scientist - Speech at Mitsubishi Electric Research Laboratories (MERL),

                                                 in  Cambridge, MA, USA

MERL's Speech & Audio Team is seeking an exceptional researcher in the areas of audio, speech, and language processing to work on robust acquisition, recognition and understanding. We are looking for candidates with a strong background in advanced machine learning techniques for speech and language processing.

Our research focuses on cutting-edge projects such as speech and sound separation, deep-learning-based microphone array processing, end-to-end speech recognition, and audio-visual question answering. As a member of our team, you will conduct original research and contribute to ongoing initiatives within the team.

Responsibilities

• Conduct innovative research aiming to redefine the cutting edge in speech and audio processing.
• Publish results in major international conferences and peer-reviewed journals.
• Maintain an influential presence in the academic community, for example via participation in technical and organizing committees.
• Assist in the patenting of developed technology and its transfer to R&D labs in Japan.

 Qualifications

• Ph.D. in Computer Science, Electrical Engineering, or a closely related field.
• Thorough knowledge and expertise in speech technologies.
• Strong publication record demonstrating innovative research achievements.
• Knowledge and experience with relevant machine learning and optimization techniques.
• Excellent programming skills, particularly in Python and deep learning toolkits.

Apply online at: https://merl.workable.com/jobs/516915/candidates/new

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Post-doctoral position in NLP

Loria a computer science lab in Nancy - France, has 12 months funded full-time post-Doctoral researcher position starting on October 2017. The post-doctoral position is funded by AMIS (Access Multilingual Information OpinionS), a Chist-Era project (http://deustotechlife.deusto.es/amis/).
The topic of the post-doc is the automatic comparison of multilingual opinions in videos. Two videos in two different languages concerning the same topic have to be compared. One of the video is summarized and translated to the language of the second one. This last one is summarized and then the opinions of the two original videos are compared in terms of emotional labels such as: anger, disgust, fear, joy, sadness, surprise... They should be compared also in terms of basic sentiments.
Social network will be used in order to reinforce the analysis of the contents in terms of opinions and sentiments.
AMIS group will make available the summary of videos in terms of text. The candidate will work on NLP, but skills in video analysis will be appreciated.
The applicant will contribute also to other tasks in collaboration with other partners of AMIS project. The successful candidate will join the SMarT research team, he will be supervised by Prof. Kamel Smaïli, Dr D. Langlois and Dr D. Jouvet. The applicant will work also with Dr O. Mella and Dr D. Fohr.
Location: Loria - Nancy (France)  Duration: October 2017 – September 2018  Net salary: from 1800 Euros to 2400 Euros per month.
The ideal applicant should have:

 
A PhD in NLP, opinion and sentiment mining or other strongly related discipline.

A very solid background in statistical machine learning.

Strong publications.        

Solid programming skills to conduct experiments.        

Excellent level in English. 

Applicants should send to smaili@loria.fr: 

A CV        

A cover letter outlining the motivation       

Three most representative papers 

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The company:

    Spitch AG (www.spitch.ch) is an international company focused on speech technologies based in Zurich, with offices in London, Moscow, Madrid, and Milan. The current position is for the Zurich headquarters.

• Job brief:

    We are looking for a Senior Research Engineer to improve our acoustic modeling and voice biometrics technologies. You will be an active member of the core R&D team and will help to develop training recipes, optimize the related existing processes and tools, and bring new technologies to the company.

    Your responsibility within the team will increase gradually: you will begin with understanding the basic technology of the company and using it to generate acoustic and speaker verification models for internal projects, and, after some adaptation time, you will work on our core technology to keep it at the state-of-the-art level.

    In this role, you should be able to work independently and also to discuss problems and solutions with the rest of the team. You should have excellent organization and problem-solving skills.

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JOB AD FALL 2017

University of Delaware seeks an assistant professor in phonetics/laboratory phonology

The Department of Linguistics and Cognitive Science at the University of Delaware invites applications for a full-time tenure-track faculty position at the rank of Assistant Professor in the area of phonetics and/or laboratory phonology.  The position will commence September 1, 2018.  The successful candidate will have a strong research program in phonetics and/or laboratory phonology and will demonstrate a commitment to excellence in teaching.  Candidates must be able to teach graduate and undergraduate courses in phonetics and ideally in phonology as well.  A secondary specialization in sociolinguistics, endangered languages, first or second language acquisition, communication disorders, or a related field is desirable.

Applicants for this position should have a PhD in Linguistics or related field, or should expect to complete their degree requirements prior to appointment. Applicants should apply on-line at http://apply.interfolio.com/ and should submit a letter of application, a curriculum vitae, a statement describing their research program, a statement of teaching experience and philosophy (including evidence of teaching ability if available), and sample publications.  They should also arrange for submission of at least three letters of recommendation. We particularly welcome applications from members of underrepresented minorities. Review of applications will begin on December 1, 2017; for fullest consideration, all application materials should be submitted by that date.  Questions should be directed to Irene Vogel at: ivogel@udel.

The University of Delaware combines leadership in research with a commitment to undergraduate and graduate education.  The main campus in Newark, Delaware provides the amenities of a vibrant college town with convenient access to the major cities of the East Coast.  The Department of Linguistics and Cognitive Science (https://www.lingcogsci.udel.edu) offers a PhD in Linguistics, a Master's degree in Linguistics and Cognitive Science, a Bachelor of Science degree in Cognitive Science (with a concentration in Pre-Professional Speech-Language Pathology), and a Bachelor of Arts degree in Linguistics. The Department is comprised of 11 full-time faculty and enrolls approximately 30 PhD students, 25 MA students, 300 undergraduate majors and 60 minors.

The University of Delaware is an equal opportunity/affirmative action employer and Title IX institution.  Employment offers will be conditioned upon successful completion of a criminal background check.  A conviction will not necessarily exclude an applicant from employment.  For the University's complete non-discrimination statement, please visit http://www.udel.edu/home/legal-notices/

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The European Language resources Distribution Agency (ELDA), a company specialized in Human Language Technologies within an international context is currently seeking to fill an immediate vacancy for a Language Resources Project Manager ? Junior position. This yields excellent opportunities for young, creative, and motivated candidates wishing to participate actively to the Language Engineering field.

Language Resources Project Manager - Junior (m/f)

Under the supervision of the Language Resources Manager, the Language Resources Project Manager ? Junior will be in charge of the identification of Language Resources (LRs), the negotiation of rights in relation with their distribution, as well as the data preparation, documentation and curation.

 The position includes, but is not limited to, the responsibility of the following tasks:

• Identification of LRs and Cataloguing
• Negotiation of distribution rights, including interaction with LR providers, drafting of distribution agreements, definition of prices of language resources to be integrated in the ELRA catalogue or for research projects
• LR Packaging within production projects
• Data preparation, documentation and curation

 Profile:

• PhD in computational linguistics or similar fields
• Experience in managing NLP tools
• Experience in project management and participation in European projects, as well as practice in contract and partnership negotiation at an international level, would be a plus
• Good knowledge of script programming (Perl, Python or other languages)
• Good knowledge of Linux
• Dynamic and communicative, flexible to combine and work on different tasks
• Ability to work independently and as part of a team
• Proficiency in English, with strong writing and documentation skills. Communication skills required in a French-speaking working environment
• Citizenship of (or residency papers) a European Union country

All positions are based in Paris. Applications will be considered until the position is filled.

Salary is commensurate with qualifications and experience.
Applicants should email a cover letter addressing the points listed above together with a curriculum vitae to:

ELDA
9, rue des Cordelières
75013 Paris
FRANCE
Fax : 01 43 13 33 30
Mail job@elda.org

ELDA is acting as the distribution agency of the European Language Resources Association (ELRA). ELRA was established in February 1995, with the support of the European Commission, to promote the development and exploitation of Language Resources (LRs). Language Resources include all data necessary for language engineering, such as monolingual and multilingual lexica, text corpora, speech databases and terminology. The role of this non-profit membership Association is to promote the production of LRs, to collect and to validate them and, foremost, make them available to users. The association also gathers information on market needs and trends.

For further information about ELDA and ELRA, visit:
http://www.elra.info

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PhD Stipend in Low-resource Keyword Spotting for Hearing Assistive Devices at Aalborg University, Denmark

Job description: Manual operation of hearing assistive devices is cumbersome in various situations. With advances in machine learning and speech technology, voice interfaces due to their convenience will be widely deployed for hearing assistive devices and they can be personalized and offer richer functionalities. Hearing assistive devices are characterized by strict memory and computational complexity constraints and the fact that they are expected to operate flawlessly, even in acoustically challenging situations. This PhD project aims to develop personalized, noise-robust and low-resource voice control systems for hearing assistive devices, using microphone signals and other modalities.

The successful applicant must have a Master degree in machine learning, statistical signal processing, speech processing or acoustic signal processing, and have extensive knowledge in one or more of these disciplines.

You may obtain further information from Professor Zheng-Hua Tan (phone: +45 9940 8686, email: zt@es.aau.dk) or Professor Jesper Jensen (phone: +45 9940 8630, email: jje@es.aau.dk).

For more details, please refer to http://www.stillinger.aau.dk/vis-stilling/?vacancy=936714.

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Postdoctoral researcher in Speech Recognition and Language Modeling

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Speech scientist at ELSA

Location: Lisbon, Portugal

contact: people@elsaspeak.com

Job Description

We are looking for an splendid Speech Scientist to join our team al ELSA and help us in our mission to help every language learner speak a foreign language fluently and confidently.

As a speech scientist al ELSA you will be playing with state-of-the-art machine learning and applying them to tons of audio and text data, towards building new technology and improving existing algorithms.

At ELSA you will not do your job alone. Solving a problem includes working with a team (backend, speech scientists, product managers, designers) to design solutions that would impact hundreds of thousands of users. We are an agile team. We are passionate engineers. We are highly collaborative. We value results. We go above and beyond to help our users and to deliver superb products, but we also value work-life balance - we are motorcycle riders, mountain climbers, food-enthusiasts, espresso lovers, yoga students, proud parents.

With more than 1.5M app downloads, your research will be directly influenced and will influence the many thousands of users that use our app daily.

Your role

• Investigate and implement new technology in speech and natural language processing.

• Postprocess, organize and put to use the myriad of data collected daily from the usage of the ELSA app.

• Propose new features and investigate their technical feasibility at scale, in a production environment. Work with the CTO and development engineers to turn research into reality.

• Work with the rest of the speech scientists to define the future of the speech and NLP technology used at ELSA.

• Maintain and improve the current speech and NLP technology stack following state-or-the-art developments and availability of new training data.

Requirements

• PhD in speech technology or related area (Masters level + related experience will also be considered).

• Proven research and publications track record that shows you can think on your own and come up with novel approaches to state-of-the-art problems.

• Outstanding coding skills. You should be able to program in low level languages like C++, high level prototyping using Python, Matlab, or similar; and be able to glue all them together using bash scripts.

• Enthusiasm and readiness to dig into production results to correct corner cases of your algorithms and iterate to better technology.

• Acquainted with deep learning open source packages (Theano, tensor flow, Caffe, Torch,...) and experience using Kaldi ASR.

What we offer

• Competitive salary and stock options according to seniority

• Company laptop

• Flexible working hours

• Ample room to grow professionally

• Experience the true startup spirit of a fast growing and well funded Silicon Valley startup

Application

Send your  LinkedIn profile or your CV to people@elsaspeak.com and we will get in touch.

About us

ELSA (English Language Speech Assistant) Corp. is a San Francisco-based startup with engineering offices in Lisbon. Our vision is to enable everyone to speak foreign languages with full confidence, reaching better life and career opportunities. Our flagship product, ELSA speak, is a personal mobile coach who improves our users' English pronunciation and intonation using phoneme and suprasegmental analysis of the user's speech signal. Our backend servers implement state-of-the-art speech recognition technology to pinpoint errors and give accurate and consistent feedback to our users on how to improve.

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Senior speech scientist at ELSA

Location: flexible, where would you like to live?

contact: people@elsaspeak.com

Job description

We are looking for an splendid Senior Speech Scientist to join our team al ELSA and help us in our mission to help every language learner speak a foreign language fluently and confidently.

As a Senior Scientist at ELSA you will be responsible for the evolution of the speech technology powering our language assessment services. Your efforts will translate directly to new voice-enabled features and better assessment quality for hundreds of thousands of language learners that use ELSA app. In addition, you will work directly with the CTO to define and drive the scientific roadmap of the company.

At ELSA you will not do your job alone.  Solving a problem includes working with a team (backend, speech scientists, product managers, designers) to design solutions that would impact hundreds of thousands of users. We are an agile team. We are passionate engineers. We are highly collaborative. We value results. We go above and beyond to help our users and to deliver superb products, but we also value work-life balance - we are motorcycle riders, mountain climbers, food-enthusiasts, espresso lovers, yoga students, proud parents.

Join our world-class team and be one of the personalities that make the ELSA culture awesome.

Requirements:

• PhD in speech technology or very related area

• 5+ years of experience post-PhD

• Expert in acoustic modeling in English

• Leadership experience leading junior researchers and students

Bonus skills

• Experience bringing products to market

• Knowledge of Kaldi-ASR package at API level

• Experience in CALL (Computer Assisted Language Learning) technology

• Good programming skills in Python, C++ and shell hacking

• Experience training multilingual ASR systems and working with languages other than English

What we offer

• Flexible working location

• Competitive salary and stock options according to seniority

• Company laptop

• Flexible working hours

• Ample room to grow professionally

• Experience the true startup spirit of a fast growing and well funded Silicon Valley startup

Application

Send your an email with your LinkedIn profile or your CV to people@elsaspeak.com and we will get back to you.

About us

ELSA Corp. is a US (San Francisco) startup with engineering offices in Lisbon. Our vision is to enable everyone to speak foreign languages with full confidence, reaching better life and career opportunities, powered by our proprietary speech recognition technology using deep learning. Our flagship product, ELSA speak, is a personal mobile coach who improves our users' English pronunciation and intonation using phonetic and suprasegmental analysis of the user's speech. Our backend servers implement state-of-the-art speech assessment technology to pinpoint the user?s most outstanding errors and give accurate and consistent feedback on how to solve them.

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Openings for two post-doctoral researchers at Idiap Research Institute.
 Both involve the theory and application of deep learning to bring speech processing to
home devices.

 http://www.idiap.ch/education-and-jobs/job-10232

Idiap is located in French speaking Switzerland, although the lab hosts many
nationalities, and functions in English.  All positions offer quite generous salaries.

The positions involve collaboration with a commercial partner located nearby. However,
they are funded by a Swiss federal grant, so a significant research element is expected.

Several similar positions at PhD, post-doc and senior level are available at the
institute in general.

 http://www.idiap.ch/en/join-us/job-opportunities

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November 2017

Postdoctoral research position: Acoustic cough detection and processing for healthcare
A postdoc position focussing on the automatic detection, analysis and classification of coughing in unconstrained audio for healthcare monitoring and disease screening is available in the Digital Signal Processing Group of the Department of Electrical and Electronic Engineering at the University of Stellenbosch, South Africa.
The project will involve the development of machine learning algorithms that are able to automatically distinguish and characterise coughing in a noisy environment, with an emphasis on the monitoring of tuberculosis. The project will also include the compilation of data corpus and collaboration with medical practitioners.
Specific project objectives include the gathering of the acoustic data, setting up and managing the annotation process, developing automatic detection and classification systems  using the gathered data, and producing new and original research into how best to automatically detect and classify coughing in a difficult acoustic environment.
Applicants must hold a PhD (preferably obtained within the last 5 years) in the field of Electronic/Electrical Engineering, Information Engineering, Computer Science, or other relevant discipline. Suitable candidates must also have practical and research experience in a relevant machine learning specialisation such as automatic speech or speaker recognition or sound event detection. The candidate should have an excellent background in statistical modelling, signal processing, and/or  audio analysis. Applicants should also have proven prior experience in data compilation,  have good programming skills and be able to use high level programming languages for developing prototype systems. Finally, candidates must have excellent English writing skills and have an explicit interest in scientific research and publication.
The position will be available for one year, with a possible extension to a second year, depending on progress and available funds.  
Applications should include a covering letter, curriculum vitae, list of publications, research projects, conference participation and details of three contactable referees and should be sent as soon as possible to: Prof Thomas Niesler, Department of Electrical and Electronic Engineering, University of Stellenbosch, Private Bag X1, Matieland 7602. Applications can also be sent by email to: trn@sun.ac.za. The successful applicant will be subject to University policies and procedures.
Interested applicants are welcome to contact me at the above e-mail address for further information regarding the project.

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Postdoctoral research position: Extremely-low-resource radio browsing for humanitarian monitoring in rural Africa

 A postdoc position focussing on automatic identification of spoken keywords in multilingual environments with extremely few or even no resources using deep neural architectures is available in the Digital Signal Processing Group of the Department of Electrical and Electronic Engineering at the University of Stellenbosch. The project will develop wordspotters that can be used to monitor community radio broadcasts in rural African regions as a source of early warning information during natural disasters, disease outbreaks, or other crises. Specific project objectives include the development of a research system, the production of associated publishable outputs. The position is part of a collaborative project with the United Nations Global Pulse. Further information is available on the web at http://pulselabkampala.ug/. Applicants should hold a PhD (obtained within the last 5 years) in the field of Electronic/Electrical Engineering, Information Engineering, or Computer Science, or other relevant disciplines. Suitable candidates must have practical experience with automatic speech recognition systems in general and deep neural net architectures in particular, and should have an excellent background in statistical modelling and machine learning. The candidate must also have good programming skills and be able to use high level programming languages for developing prototype systems. Finally, candidates must have excellent English writing skills and have an explicit interest in scientific research and publication.
The position will be available for one year, with a possible extension to a second year, depending on progress and available funds.  
Applications should include a covering letter, curriculum vitae, list of publications, research projects, conference participation and details of three contactable referees and should be sent as soon as possible to: Prof Thomas Niesler, Department of Electrical and Electronic Engineering, University of Stellenbosch, Private Bag X1, Matieland 7602. Applications can also be sent by email to: trn@sun.ac.za. The successful applicant will be subject to University policies and procedures.
Interested applicants are welcome to contact me at the above e-mail address for further information regarding the project.

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Le réseau de formation sur le traitement automatique de la parole pathologique (TAPAS) est un projet H2020 MSCA-ITN-ETN qui fournira à 15 doctorants une formation large et intensive sur le traitement de la parole pathologique. Le consortium du projet TAPAS comprend des praticiens cliniques, des chercheurs universitaires et des partenaires industriels, avec une expertise couvrant l'ingénierie de la parole, la linguistique et la science clinique. Le programme de travail TAPAS est organisé autour de trois grands thèmes:

- Détection de la parole pathologique (4 thèses)

- Évaluation de la parole pathologique et thérapie (6 thèses)

- Technologies de communication pour la vie assistée et la réadaptation (5 thèses)

Le consortium TAPAS comprend:
-Idiap Research Institute (CH)
-Friedrich-Alexander-Univeristaet (DE)
-Interuniversitair Micro-Electronicacentrum IMEC VZW (BE)
-INESC ID - Instituto de Engenhariade Sistemas E Computabores Investigacao E Desenvolvimento em Lisboa (PT)
-Ludwig-Maximilians-Universitaet Muenchen (DE),
-Stichting Het Nederlands Kanker Instituut-Antoni Van Leeuwenhoek Ziekenhuis (NL), 
-Philips Electronics Nederland B.V. (NL), 
-Stichting Katholieke Universiteit (NL)
-Universität Augsburg (DE), 
-Université Toulouse III-Paul Sabatier (FR), 
-The University of Sheffield United Kingdom (UK), 
-Universitair Ziekenhuis Antwerpen (BE)

Pour plus d?informations et pour candidater, veuillez vous référer au site http://www.tapas-etn-eu.org 

Bien cordialement,

Julie Mauclair
MCF  IRI
Université Paris Descartes

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Visiting Assistant Professor in Computational Linguistics and Language Science

URL:

http://apptrkr.com/1116774


 Requisition Number: 3499BR

Detailed Job Description:

The Department of English invites applications for a Visiting Assistant Professor position, beginning in January 2018, with specialization in computational linguistics and/or innovative technical or scientific methods in language science at Rochester Institute of Technology (RIT), with a focus on one or more areas of application. Possible areas include:

·  Deep learning for natural language understanding

·  Speech and speech technology

·  Multimodal and linguistic sensors

·  Human-computer interaction

·  Linguistic narrative analytics

The applicant should demonstrate a fit with our commitment to collaborate with colleagues across the university on initiatives in artificial intelligence and in digital humanities and social sciences. The position has the possibility of extension beyond Spring 2018.

The successful applicant will be a researcher and teacher with an agenda that emphasizes innovative technical methods in linguistics, for instance in natural language processing, linguistic/multimodal sensors, speech and speech technology, and/or other computational or technical approaches applied to language data. We are seeking a scholar who engages in disciplinary and interdisciplinary teamwork, student mentoring, and has a coherent plan for grant seeking activities. The right candidate will contribute to advancing our interdisciplinary language science curriculum in a college of liberal arts at a technical university. Contributions that build students' global education experiences are additionally valued.

The teaching assignment may be Introduction to Language Science, Language Technology, Introduction to NLP, Science and Analytics of Speech (acoustic and experimental phonetics), Spoken Language Processing (automatic speech recognition and text-to-speech synthesis), Seminar in Computational Linguistics, self-designed courses, or another course depending on background.

We are seeking an individual who has the ability and interest in contributing to a community committed to student-centeredness; professional development and scholarship; integrity and ethics; respect, diversity and pluralism; innovation and flexibility; and teamwork and collaboration. Select to view links to RIT's core values, honor code, and statement of diversity.

Department Description:

THE UNIVERSITY AND ROCHESTER COMMUNITY:
RIT is a national leader in professional and career-oriented education. Talented, ambitious, and creative students of all cultures and backgrounds from all 50 states and more than 100 countries have chosen to attend RIT. Founded in 1829, Rochester Institute of Technology is a privately endowed, coeducational university with nine colleges emphasizing career education and experiential learning. With approximately 15,000 undergraduates and 2,900 graduate students, RIT is one of the largest private universities in the nation. RIT offers a rich array of degree programs in engineering, science, business, and the arts, and is home to the National Technical Institute for the Deaf. RIT has been honored by The Chronicle of Higher Education as one of the ?Great Colleges to Work For? for four years. RIT is a National Science Foundation ADVANCE Institutional Transformation site. RIT is responsive to the needs of dual-career couples by our membership in the Upstate NY HERC.

Rochester, situated between Lake Ontario and the Finger Lakes region, is the 51st largest metro area in the United States and the third largest city in New York State. The Greater Rochester region, which is home to nearly 1.1 million people, is rich in cultural and ethnic diversity, with a population comprised of approximately 18% African and Latin Americans and another 3% of international origin. It is also home to one of the largest deaf communities per capita in the U.S. Rochester ranks 4th for ?Most Affordable City' by Forbes Magazine, and MSN selected Rochester as the ?#1 Most Livable Bargain Market? (for real-estate). Kiplinger named Rochester one of the top five ?Best City for Families.?

Job Requirements:

·  Ph.D. with training in Computational Linguistics, Linguistics, or an allied field for language science, in hand prior to appointment date.

·  Advanced graduate coursework in computational linguistics, including natural language and/or spoken language processing or technical methods in linguistics.

·  Publication record and coherent plan for research and grant seeking activities.

·  Evidence of outstanding teaching.

·  Ability to contribute in meaningful ways to the college's continuing commitment to cultural diversity, pluralism, and individual differences.

How to Apply:

Apply online at  http://apptrkr.com/1116774. Please submit your online application, curriculum vitae, cover letter addressing the listed qualifications and upload the following attachments:

·  A research statement

·  A teaching statement

·  Copy of transcripts of graduate coursework

·  A sample publication 

·  The names, addresses, and phone numbers for three references
·  Statement of diversity

Questions regarding this position can be directed to the search committee chair-Dr. Cecilia Ovesdotter Alm at coagla@rit.edu.

Review of applications will begin on November 25, 2017 and will continue until an acceptable candidate is found.

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Principal Speech Recognition Engineer

Location: Cambridge, UK

Contact: careers@speechmatics.com

Background

Speechmatics’ versatile automatic speech recognition technology, based on decades of research and experience in neural networks, is enabling world-leading companies to power a speech-enabled future. Having already transcribed millions of hours of audio and helped customers across a diverse range of use cases and applications, the team’s mission is to build the best speech technology for any application, anywhere, in any language and put speech back at the heart of communication.

In the office, we pride ourselves on a relaxed but productive environment enabling both commercial success and personal development - we often host lunch and learn sessions and attend regular academic and commercial conferences. When we're not working hard, we regularly host company outings and events where your plus-one is welcomed to enjoy great food, great drinks, and great company! We also reward ourselves occasionally with massages, and even get our bikes fixed onsite!

We think it’s important to give a little back too, so everyone is eligible for some time off for charity work plus we’ll match your contribution via the Give As You Earn scheme. See more about our great perks below!

We are expanding rapidly and are seeking talented people to join us as we continue to push the boundaries of speech recognition. This is an opportunity to join a high growth team and form a major part of its future direction.

The Opportunity

We are looking for a talented and experienced speech recognition engineer to help us build the best speech technology for anybody, anywhere, in any language. You will be a part of a team that is building languages packs and developing our core ASR capabilities including improving our speed, accuracy and support for all languages. Your work will feed into the ‘Automatic Linguist’, our ground-breaking framework to support the building of ASR models and hence the delivery of every language pack published by the company. Alongside the wider team you will be responsible for keeping our system the most accurate and useful commercial speech recognition available.

Because you will be joining a rapidly expanding team, you will need to be a team player, who thrives in a fast paced environment, with a focus on rapidly moving research developments into products. We strongly encourage versatility and knowledge transfer within the team, so we can share efficiently what needs to be done to meet our commitments to the rest of the company.

Key Responsibilities

• Delivering the artefacts comprising high quality speech recognition software products

• Keeping us ahead of the rest of the world in terms of speech recognition capabilities

• Transferring knowledge to the wider team and company

Experience

Essential

• Proven track record as one of the best in the world at modern LVCSR

• Extensive practical experience of speech recognition, covering all aspects (acoustic, pronunciation and language modelling as well as decoders / search)

• Experience working with standard speech and ML toolkits, e.t., Kaldi, KenLM, TensorFlow, etc.

• Solid Python programming skills

• Experience using Unix / Linux systems

• Proven ability to effectively communicate highly technical subjects

Desirable

• Expertise in all aspects of modern speech recognition, including WFSTs, lattice processing, neural nets (RNN / DNN / LSTM etc.), etc.

• Knowledge of computational linguistics.

• Deep production-grade software development experience, especially with Python, C/C++ and / or Go.

• Experience working effectively with software engineering teams or as a Software Engineer.

• Experience of team leadership and line management

• Experience working in an Agile framework

Salary

We offer a competitive salary and bonus scheme, pension contribution matching and a generous EMI share option scheme. We also have several additional benefits including private medical insurance, holiday purchase, life assurance, childcare vouchers, cycle scheme, massages, bike doctor, fully stocked drinks fridge, and fresh fruit available daily to name just a few!

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Principal Language Modelling Engineer

Location: Cambridge, UK

Contact: careers@speechmatics.com

Background

Speechmatics’ versatile automatic speech recognition technology, based on decades of research and experience in neural networks, is enabling world-leading companies to power a speech-enabled future. Having already transcribed millions of hours of audio and helped customers across a diverse range of use cases and applications, the team’s mission is to build the best speech technology for any application, anywhere, in any language and put speech back at the heart of communication.

In the office, we pride ourselves on a relaxed but productive environment enabling both commercial success and personal development - we often host lunch and learn sessions and attend regular academic and commercial conferences. When we're not working hard, we regularly host company outings and events where your plus-one is welcomed to enjoy great food, great drinks, and great company! We also reward ourselves occasionally with massages, and even get our bikes fixed onsite!

We think it’s important to give a little back too, so everyone is eligible for some time off for charity work plus we’ll match your contribution via the Give As You Earn scheme. See more about our great perks below!

We are expanding rapidly and are seeking talented people to join us as we continue to push the boundaries of speech recognition. This is an opportunity to join a high growth team and form a major part of its future direction.

The Opportunity

We are looking for a talented and experienced Language Modelling expert to help us build the best speech technology for anybody, anywhere, in any language. You will be a part of a team that is working on our core ASR capabilities to improve our speed, accuracy and support for all languages. Your role will include making sure our Language Modelling capability remains at the head of the field. Your work will feed into the ‘Automatic Linguist’, our ground-breaking framework to support the building of ASR models, and hence the delivery of every language pack published by the company. Alongside the wider team you will be responsible for keeping our system the most accurate and useful commercial speech recognition available.

Because you will be joining a rapidly expanding team, you will need to be a team player who thrives in a fast paced environment, with a focus on rapidly moving research developments into products. We strongly encourage versatility and knowledge transfer within the team, so we can share efficiently what needs to be done to meet our commitments to the rest of the company.

Key Responsibilities

• Analysing advances in the field of ASR – especially language modelling – and reporting back on what is the latest and greatest

• Ensuring we can implement the best ASR technology in a production environment

• Leading the language modelling extension of our ML framework

• Being part of a team delivering all the artefacts required to make up the best speech recognition available to our customers

Experience

Essential

• Proven track record as one of the best in the world at modern language modelling techniques for LVCSR

• Proven ability to effectively communicate highly technical subjects

Desirable

• MSc, PhD or equivalent qualification in the academic aspects of speech recognition

• Extensive experience working with standard language modelling and ML toolkits, e.g. pocolm, KenLM, SRILM, TensorFlow, etc.

• Expertise in all aspects of modern speech recognition, including WFSTs, lattice processing, neural net (RNN / DNN / LSTM), acoustic and language models, Viterbi decoding

• Experience translating academic advances in ASR into production systems

• Comprehensive knowledge of machine learning and statistical modelling

• Expertise in Python and/or C++ software development

• Experience working effectively with software engineering teams or as a Software Engineer

• Experience of technical leadership of a team / teams

• Experience of team leadership and line management

• Experience of working in an Agile framework

Salary

We offer a competitive salary and bonus scheme, pension contribution matching and a generous EMI share option scheme. We also have several additional benefits including private medical insurance, holiday purchase, life assurance, childcare vouchers, cycle scheme, massages, bike doctor, fully stocked drinks fridge, and fresh fruit available daily to name just a few!

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Principal Acoustic Modelling Engineer

Location: Cambridge, UK

Contact: careers@speechmatics.com

Background

Speechmatics’ versatile automatic speech recognition technology, based on decades of research and experience in neural networks, is enabling world-leading companies to power a speech-enabled future. Having already transcribed millions of hours of audio and helped customers across a diverse range of use cases and applications, the team’s mission is to build the best speech technology for any application, anywhere, in any language and put speech back at the heart of communication.

In the office, we pride ourselves on a relaxed but productive environment enabling both commercial success and personal development - we often host lunch and learn sessions and attend regular academic and commercial conferences. When we're not working hard, we regularly host company outings and events where your plus-one is welcomed to enjoy great food, great drinks, and great company! We also reward ourselves occasionally with massages, and even get our bikes fixed onsite!

We think it’s important to give a little back too, so everyone is eligible for some time off for charity work plus we’ll match your contribution via the Give As You Earn scheme. See more about our great perks below!

We are expanding rapidly and are seeking talented people to join us as we continue to push the boundaries of speech recognition. This is an opportunity to join a high growth team and form a major part of its future direction.

The Opportunity

We are looking for a talented and experienced Acoustic Modelling expert to help us build the best speech technology for anybody, anywhere, in any language. You will be a part of a team that is working on our core ASR capabilities to improve our speed, accuracy and support for all languages. Your role will include making sure our Acoustic Modelling capability remains at the head of the field. Your work will feed into the ‘Automatic Linguist’, our ground-breaking framework to support the building of ASR models, and hence the delivery of every language pack published by the company. Alongside the wider team you will be responsible for keeping our system the most accurate and useful commercial speech recognition available.

Because you will be joining a rapidly expanding team, you will need to be a team player who thrives in a fast paced environment, with a focus on rapidly moving research developments into products. We strongly encourage versatility and knowledge transfer within the team, so we can share efficiently what needs to be done to meet our commitments to the rest of the company.

Key Responsibilities

• Analysing advances in the field of ASR – especially acoustic modelling – and reporting back on what is the latest and greatest

• Ensuring we can implement the best ASR technology in a production environment

• Leading the acoustic modelling extension of our ML framework

• Being part of a team delivering all the artefacts required to make up the best speech recognition available to our customers

Experience

Essential

• Proven track record as one of the best in the world at modern language modelling techniques for LVCSR

• Proven ability to effectively communicate highly technical subjects

Desirable

• MSc, PhD or equivalent qualification in the academic aspects of speech recognition

• Extensive experience working with standard acoustic modelling and ML toolkits, e.g. Kaldi, TensorFlow, etc.

• Expertise in all aspects of modern speech recognition, including WFSTs, lattice processing, neural net (RNN / DNN / LSTM), acoustic and language models, Viterbi decoding

• Experience translating academic advances in ASR into production systems

• Comprehensive knowledge of machine learning and statistical modelling

• Expertise in Python and/or C++ software development

• Experience working effectively with software engineering teams or as a Software Engineer

• Experience of technical leadership of a team / teams

• Experience of team leadership and line management

• Experience of working in an Agile framework

Salary

We offer a competitive salary and bonus scheme, pension contribution matching and a generous EMI share option scheme. We also have several additional benefits including private medical insurance, holiday purchase, life assurance, childcare vouchers, cycle scheme, massages, bike doctor, fully stocked drinks fridge, and fresh fruit available daily to name just a few!

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Speech Recognition Intern

Location: Cambridge, UK

Contact: careers@speechmatics.com

Background

Speechmatics’ versatile automatic speech recognition technology, based on decades of research and experience in neural networks, is enabling world-leading companies to power a speech-enabled future. Having already transcribed millions of hours of audio and helped customers across a diverse range of use cases and applications, the team’s mission is to build the best speech technology for any application, anywhere, in any language and put speech back at the heart of communication.

In the office, we pride ourselves on a relaxed but productive environment enabling both commercial success and personal development - we often host lunch and learn sessions and attend regular academic and commercial conferences. When we’re not working hard, we regularly host company outings and events where your plus-one is welcomed to enjoy great food, great drinks and great company! We also reward ourselves occasionally with massages, and even get our bikes fixed onsite!

We are expanding rapidly and are seeking talented people to join us as we continue to push the boundaries of speech recognition. This is an opportunity to join a high growth team and form a major part of its future direction.

The Opportunity

We are looking for a bright, enthusiastic and talented speech recognition intern to help us build the best speech technology for anybody, anywhere, in any language. You will be a part of a team that is building languages packs and developing our core ASR capabilities including improving our speed, accuracy and support for all languages. Your work will feed into the ‘Automatic Linguist’, our ground-breaking framework to support the building of ASR models and hence the delivery of every language pack published by the company. Alongside the wider team you will be responsible for keeping our system the most accurate and useful commercial speech recognition available.

Because you will be joining a rapidly expanding team, you will need to be a team player who thrives in a fast paced environment, happy to pick up whatever needs to be done, with a focus on rapidly moving research developments into products. We strongly encourage versatility and knowledge transfer within the team, so we can share efficiently what needs to be done to meet our commitments to the rest of the company.

Key Responsibilities

• Delivering high quality speech recognition products

• Keeping us ahead of the rest of the world in terms of speech recognition capabilities

• Learning!

Experience

Essential

• Interest in speech recognition

• Experience using Python

• Experience using Unix / Linux systems

• A team player willing to contribute to all sprint activities

Desirable

• Experience in Speech recognition or related fields

• Experience working with standard speech and ML toolkits, e.g. Kaldi, KenLM, TensorFlow, etc.

• Knowledge of computational linguistics.

• Knowledge of modern software development practices

Salary

This will be a paid internship. We also have several additional benefits including massages, bike doctor, fully stocked drinks fridge, and fresh fruit available daily to name just a few!

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Speech Recognition Engineer

Location: Cambridge, UK

Contact: careers@speechmatics.com

Background

Speechmatics’ versatile automatic speech recognition technology, based on decades of research and experience in neural networks, is enabling world-leading companies to power a speech-enabled future. Having already transcribed millions of hours of audio and helped customers across a diverse range of use cases and applications, the team’s mission is to build the best speech technology for any application, anywhere, in any language and put speech back at the heart of communication.

In the office, we pride ourselves on a relaxed but productive environment enabling both commercial success and personal development - we often host lunch and learn sessions and attend regular academic and commercial conferences. When we're not working hard, we regularly host company outings and events where your plus-one is welcomed to enjoy great food, great drinks, and great company! We also reward ourselves occasionally with massages, and even get our bikes fixed onsite!

We think it’s important to give a little back too, so everyone is eligible for some time off for charity work plus we’ll match your contribution via the Give As You Earn scheme. See more about our great perks below!

We are expanding rapidly and are seeking talented people to join us as we continue to push the boundaries of speech recognition. This is an opportunity to join a high growth team and form a major part of its future direction.

The Opportunity

We are looking for a talented speech recognition engineer to help us build the best speech technology for anybody, anywhere, in any language. You will be a part of a team that is building languages packs and developing our core ASR capabilities including improving our speed, accuracy and support for all languages. Your work will feed into the ‘Automatic Linguist’, our ground-breaking framework to support the building of ASR models and hence the delivery of every language pack published by the company. Alongside the wider team you will be responsible for keeping our system the most accurate and useful commercial speech recognition available.

Because you will be joining a rapidly expanding team, you will need to be a team player who thrives in a fast paced environment happy to pick up whatever needs to be done, with a focus on rapidly moving research developments into products. We strongly encourage versatility and knowledge transfer within the team, so we can share efficiently what needs to be done to meet our commitments to the rest of the company.

Key Responsibilities

• Delivering high quality speech recognition products

• Keeping us ahead of the rest of the world in terms of speech recognition capabilities

Experience

Essential

• Practical experience of speech recognition or a related field with crossover knowledge

• Interest in speech recognition

• Experience using Python

• Experience using Unix / Linux systems

• A team player willing to contribute to all sprint activities

Desirable

• Experience in modern speech recognition, such as WFSTs, lattice processing, neural nets (RNN / DNN / LSTM etc.), acoustic and language modelling, etc.

• Experience working with standard speech and ML toolkits, e.g. Kaldi, KenLM, TensorFlow, etc.

• Knowledge of computational linguistics.

• Production-grade software development experience, especially with Python, C/C++ and / or Go.

• Experience working effectively with software engineering teams or as a Software Engineer.

• Experience working in an Agile framework

Salary

We offer a competitive salary and bonus scheme, pension contribution matching and a generous EMI share option scheme. We also have several additional benefits including private medical insurance, holiday purchase, life assurance, childcare vouchers, cycle scheme, massages, bike doctor, fully stocked drinks fridge, and fresh fruit available daily to name just a few!

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Senior Speech Recognition Engineer

Location: Cambridge, UK

Contact: careers@speechmatics.com

Background

Speechmatics’ versatile automatic speech recognition technology, based on decades of research and experience in neural networks, is enabling world-leading companies to power a speech-enabled future. Having already transcribed millions of hours of audio and helped customers across a diverse range of use cases and applications, the team’s mission is to build the best speech technology for any application, anywhere, in any language and put speech back at the heart of communication.

In the office, we pride ourselves on a relaxed but productive environment enabling both commercial success and personal development - we often host lunch and learn sessions and attend regular academic and commercial conferences. When we're not working hard, we regularly host company outings and events where your plus-one is welcomed to enjoy great food, great drinks, and great company! We also reward ourselves occasionally with massages, and even get our bikes fixed onsite!

We think it’s important to give a little back too, so everyone is eligible for some time off for charity work plus we’ll match your contribution via the Give As You Earn scheme. See more about our great perks below!

We are expanding rapidly and are seeking talented people to join us as we continue to push the boundaries of speech recognition. This is an opportunity to join a high growth team and form a major part of its future direction.

The Opportunity

We are looking for a talented and experienced speech recognition engineer to help us build the best speech technology for anybody, anywhere, in any language. You will be a part of a team that is building languages packs and developing our core ASR capabilities including improving our speed, accuracy and support for all languages. Your work will feed into the ‘Automatic Linguist’, our ground-breaking framework to support the building of ASR models and hence the delivery of every language pack published by the company. Alongside the wider team you will be responsible for keeping our system the most accurate and useful commercial speech recognition available.

Because you will be joining a rapidly expanding team, you will need to be a team player who thrives in a fast paced environment, happy to pick up whatever needs to be done, with a focus on rapidly moving research developments into products. We strongly encourage versatility and knowledge transfer within the team, so we can share efficiently what needs to be done to meet our commitments to the rest of the company.

Key Responsibilities

• Delivering the artefacts comprising high quality speech recognition software products

• Keeping us ahead of the rest of the world in terms of speech recognition capabilities

• Transferring knowledge to the wider team and company

Experience

Essential

• Practical experience of speech recognition, covering all aspects (acoustic, pronunciation and language modelling as well as decoders / search)

• Experience working with standard speech and ML toolkits, e.g., Kaldi, KenLM, TensorFlow, etc.

• Solid Python programming skills

• Experience using Unix / Linux systems

• A team player willing to contribute to all sprint activities

• Ability to effectively communicate highly technical subjects

Desirable

• Expertise in all aspects of modern speech recognition, including WFSTs, lattice processing, neural nets (RNN / DNN / LSTM etc.), etc.

• Knowledge of computational linguistics.

• Deep production-grade software development experience, especially with Python, C/C++ and / or Go.

• Experience working effectively with software engineering teams or as a Software Engineer.

• Experience of team leadership and line management

• Experience working in an Agile framework

Salary

We offer a competitive salary and bonus scheme, pension contribution matching and a generous EMI share option scheme. We also have several additional benefits including private medical insurance, holiday purchase, life assurance, childcare vouchers, cycle scheme, massages, bike doctor, fully stocked drinks fridge, and fresh fruit available daily to name just a few!

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nceThe European Language resources Distribution Agency (ELDA), a company specialized in Human Language Technologies within an international context is currently seeking to fill an immediate vacancy for a Language Resources Project Manager ? Junior position. This yields excellent opportunities for young, creative, and motivated candidates wishing to participate actively to the Language Engineering field.

Language Resources Project Manager - Junior (m/f)

Under the supervision of the Language Resources Manager, the Language Resources Project Manager ? Junior will be in charge of the identification of Language Resources (LRs), the negotiation of rights in relation with their distribution, as well as the data preparation, documentation and curation.

 The position includes, but is not limited to, the responsibility of the following tasks:

• Identification of LRs and Cataloguing
• Negotiation of distribution rights, including interaction with LR providers, drafting of distribution agreements, definition of prices of language resources to be integrated in the ELRA catalogue or for research projects
• LR Packaging within production projects
• Data preparation, documentation and curation

 Profile:

• PhD in computational linguistics or similar fields
• Experience in managing NLP tools
• Experience in project management and participation in European projects, as well as practice in contract and partnership negotiation at an international level, would be a plus
• Good knowledge of script programming (Perl, Python or other languages)
• Good knowledge of Linux
• Dynamic and communicative, flexible to combine and work on different tasks
• Ability to work independently and as part of a team
• Proficiency in English, with strong writing and documentation skills. Communication skills required in a French-speaking working environment
• Citizenship of (or residency papers) a European Union country

All positions are based in Paris. Applications will be considered until the position is filled.

Salary is commensurate with qualifications and experience.
Applicants should email a cover letter addressing the points listed above together with a curriculum vitae to:

ELDA
9, rue des Cordelières
75013 Paris
FRANCE
Fax : 01 43 13 33 30
Mail job@elda.org

ELDA is acting as the distribution agency of the European Language Resources Association (ELRA). ELRA was established in February 1995, with the support of the European Commission, to promote the development and exploitation of Language Resources (LRs). Language Resources include all data necessary for language engineering, such as monolingual and multilingual lexica, text corpora, speech databases and terminology. The role of this non-profit membership Association is to promote the production of LRs, to collect and to validate them and, foremost, make them available to users. The association also gathers information on market needs and trends.

For further information about ELDA and ELRA, visit:
http://www.elra.info

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Title: 2018 PHD RESEARCH FELLOWSHIPS ( ML/Dialogue/Language/Speech)
Location: University of Trento , Italy

You may have enjoyed reading about bots, artificial intelligence, machine learning,
digital assistants, systems that support doctors, teachers, customers and help people.
Then, you would like to consider taking a front row seat and join the research team
that has been training intelligent machines and evaluating AI-based systems
for more than two decades, collaborating with best research labs in the world and
deployed them in the real-world.

Here is a sample of the projects ( http://sisl.disi.unitn.it/demo/ ) the Signals
and Interactive Systems Lab (University of Trento, Italy) has been leading:

-Natural Language Understanding systems for massive amount of human language data:
http://www.sensei-conversation.eu

-Amazon Alexa challenge on Conversational Systems:
http://sisl.disi.unitn.it/university-of-trento-is-selected-by-amazon-for-the-alexa-challenge/

-Designing AI personal agents for healthcare domain:
http://sisl.disi.unitn.it/pha/

We are looking for top-candidates for its funded PhD research fellowships.
Candidates should have background at least in one of the following areas:


- Speech Processing

- Natural Language Understanding

- Conversational Systems

- Machine Learning

Candidates will be working on research domains such as Conversational Agents,
Intelligent Systems, Speech/Text Document Mining and Summarization,
Human Behavior Understanding, Crowd Computing and AI-based systems for tutoring.


For more info on research and projects visit the lab website
Visit lab website at http://sisl.disi.unitn.it/

The SIS Lab research is driven by an interdisciplinary approach to research,
attracting researchers from  disciplines such as Digital Signal Processing,
Speech Processing, Computational Linguistics, Psychology, Neuroscience and
Machine Learning.

The  official language ( research and teaching ) of the department is English.

FELLOWSHIP

Gross amount of the fellowships ( internship and PhD ) is competitive and approximately
1.600 Euro/month.
Students may qualify for reduced campus lodging, transportation and cafeteria
reduced rates.

For more information about cost of living, campus, graduate education programs,
please visit the graduate school website at http://ict.unitn.it/

DEADLINES

Immediate openings with start date as early as March 2018.  Open until filled.

REQUIREMENTS

Strict requirement is at least Master level degree in Computer Science, Electrical
Engineering, Computational Linguistics or similar or affine disciplines. Students with
other background
(Physics, Applied Math) may apply as well. Background in at least one of the posted
research areas is required. All applicants should have good very programming, math skills
and used to team work.

HOW TO APPLY

Interested applicants should send their
1) CV
2) Statement of research interest and
3) three reference letters sent to:

Email: sisl-jobs@disi.unitn.it


For more info:

Signals and Interactive Systems Lab : http://sisl.disi.unitn.it/

PhD School : http://ict.unitn.it/

Department : http://disi.unitn.it/


Information Engineering and Computer Science Department (DISI)

DISI has a strong focus on cross-disciplinarity with professors from different
faculties of the University (Physical Science, Electrical Engineering, Economics,
Social Science, Cognitive Science, Computer Science) with international
background. DISI aims at exploiting the complementary experiences present in the
various research areas in order to develop innovative methods, technologies and
applications.

University of Trento

The University of Trento is consistently ranked as premiere Italian university
institution.
See http://www.unitn.it/en/node/1636/mid/2573

University of Trento is an equal opportunity employer.

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Audio Signal Processing Maverick (Applied Research)

ASR research is sadly mostly largely done in big companies. Sure, talent is around, but it's really only in a less crowded space that you can really shine and see the impact that you can do. A.K.A. an early-stage startup, when you’re still a group of friends with a crazy ambition to change the world.

Here’s what drives us nuts: Products where ASR is really the key component are 99% of the time made for: *answering quick/superficial requests from lazy users (Siri, Google Now, Cortana, Echo) *dealing with angry customers on the phone (all the IVRs) *dictating emails for busy people (Nuance)

What if you could truly change 400M lives instead? Turn a lifetime of frustration into a deep connection?

Ava aims at captioning the world to make it fully accessible, 24/7, to deaf & hard-of-hearing people. Mobile-first, the app is the fastest & most advanced captioning system in the world, beating what tech giants have done, by cleverly using speech and speaker identification technologies to make conversations between deaf & hard-of-hearing people and hearing people possible.

At Ava, the CEO is the only hearing person in a family of deaf people, and the CTO is deaf and non-speaking - both were Forbes 30 under 30 2017. We use our ASR-based product everyday to communicate. Our motivations are aligned with the change we want to make in the world. We care about the millions of people out there who struggle everyday to just have a social & professional life and that YOUR tech will help. If it wasn't for Ava, the next best solution would take 10X time (it's not a solution) or 100X cost (it's not accessible to all). We’re working with companies such as GE, Nike, Salesforce, but also universities, stores, and even churches to fulfill our mission to make the world truly accessible.

What we need to get to the next level? You - someone with prior research experience in audio signal processing. The core mission will be to enhance a speech recognition system used in real world cocktail party situations. The signal is acquired via an array of ad-hoc microphones, and is processed to optimize its quality for the transcription, using a set of techniques: source localization, Time Difference of Arrival, noise cancelling, source separation… all in real time.

Interested to learn more about it? Let’s chat.

Especially if:

● You just finished a PhD in audio signal processing.

● You’re ready to be a pioneer in the field, and do what is necessary to make things work in real world situations.

● You're of the persistent, yet open-minded and collaborative type: you reason by independent thinking first, but you know that together, we're stronger. What you get

● Early-stage -> massive equity opportunity.

● An opportunity to apply cutting-edge technologies to solve real world problems, right now

● Competitive salary The job will be based in our Paris office.

Interested? Let us know at alex@ava.me

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Speaker Identification Maverick (Applied Research) 

 ASR research is sadly mostly largely done in big companies. Sure, talent is around, but it's really only in a less crowded space that you can really shine and see the impact that you can do. A.K.A. an early-stage startup, when you’re still a group of friends with a crazy ambition to change the world. 
 Here’s what drives us nuts: Products where ASR is really the key component are 99% of the time made for: *answering quick/superficial requests from lazy users (Siri, Google Now, Cortana, Echo) *dealing with angry customers on the phone (all the IVRs) *dictating emails for busy people (Nuance)
 What if you could truly change 400M lives instead? Turn a lifetime of frustration into a deep connection?
 Ava aims at captioning the world to make it fully accessible, 24/7, to deaf & hard-of-hearing people. Mobile-first, the app is the fastest & most advanced captioning system in the world, beating what tech giants have done, by cleverly using speech and speaker identification technologies to make conversations between deaf & hard-of-hearing people and hearing people possible.
 At Ava, the CEO is the only hearing person in a family of deaf people, and the CTO is deaf and non-speaking - both were Forbes 30 under 30 2017. We use our ASR-based product everyday to communicate. Our motivations are aligned with the change we want to make in the world. We care about the millions of people out there who struggle everyday to just have a social & professional life and that YOUR tech will help. If it wasn't for Ava, the next best solution would take 10X time (it's not a solution) or 100X cost (it's not accessible to all). We’re working with companies such as GE, Nike, Salesforce, but also universities, stores, and even churches to fulfill our mission to make the world truly accessible.
 What we need to get to the next level? You - someone with prior research exposure to speaker identification (deep learning interest/experience is a big plus). The core of your mission will be to reinvent what voice recognition can do to understand real world conversations: crack the cocktail-party problem.
 Interested to learn more about it? Let’s chat.
Especially if:

● You just finished a PhD in Machine Learning.

● Experience in Speaker Identification, ASR, NLP, acoustic modeling, language models or source separation is a plus.

● You ambition to be a pioneer in the field, and do what is necessary to make things work in real world situations.

● You're of the persistent, yet open-minded and collaborative type: you reason by independent thinking first, but you know that together, we're stronger.

What we offer

● Early-stage -> massive equity opportunity.

● An opportunity to apply cutting-edge technologies to solve real world problems, right now

● Competitive salary The job will be based in our Paris office.

Interested? Let us know at alex@ava.me.

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PhD position in Opinion Analysis in human-agent interactions

Telecom ParisTech [1]

46 rue Barrault  75013 Paris ? France

Starting date: from Now to Early Autumn 2018

Possibility to start with an internship during first semester 2018.

Duration of the PhD funding: 36 months

*Position description* 

The PhD student will take part in the ANR JCJC MAOI (Multimodal Analysis of Opinions in Interactions) at Telecom-ParisTech. He/She will tackle the following challenging issue: the integration of opinion mining methods in human-agent interactions (i.e. companion robots or virtual vocal assistants such as Siri, Google Now, Cortana, etc.)

The role of the PhD will consist in developing machine learning methods for the multimodal (i.e. speech and text) analysis of the user?s opinion during his/her interaction with an agent. The main challenge will be to integrate the interaction context in machine-learning opinion detection methods. 

The work will include:

- the development of machine learning/deep learning approaches (Conditional Random Fields, Long-Short-Term-Memory networks)

- the integration of complex and interactional linguistic features in machine-learning models for the detection of opinions in interactions

- the integration of acoustic features in multimodal models

- the evaluation of the system in interaction context.

The PhD will join the Social Computing topic [2] in the S2a group [3] at Telecom-ParisTech.

Selected references for this position from [4] :

Barriere, V., Clavel, C., and Essid, E. (2017). Opinion dynamics modeling for movie review transcripts classification with hidden conditional random fields. Interspeech.

Clavel, C.; Callejas, Z., Sentiment analysis: from opinion mining to human-agent interaction, Affective Computing, IEEE Transactions on, 7.1 (2016): 74-93

Langlet, C. and Clavel, C. (2015). Improving social relationships in face-to-face human-agent interactions: when the agent wants to know user?s likes and dislikes. In ACL, Beijin, China.

Langlet, C. and Clavel, C. (2016). Grounding the detection of the user?s likes and dislikes on the topic structure of human-agent interactions. Knowledge-Based Systems.

* Candidate profile*

As a minimum requirement, the successful candidate will have:

?    A master degree or equivalent in one or more of the following areas: machine

learning, natural language processing, affective computing

?    Excellent programming skills (preferably in Python)

?    Good command of English

The ideal candidate will also (optionally) have:

?    Knowledge in natural language processing

?    Knowledge in probabilistic graphical models and deep learning

-- More about the position

?    Place of work: Paris, France

?    For more information about Telecom ParisTech see [1]

-- How to apply

Applications are to be sent to Chloé Clavel [4]

The application should be formatted as a single pdf file and should include:

?    A complete and detailed curriculum vitae

?    A letter of motivation

?    The transcript of grades  

?    The names and addresses of two referees

[1] https://www.telecom-paristech.fr/eng/  

[2] https://www.tsi.telecom-paristech.fr/recherche/themes-de-recherche/analyse-automatique-des-donnees-sociales-social-computing/ 

[3] http://www.tsi.telecom-paristech.fr/ssa/# 

[4] https://clavel.wp.imt.fr/publications/

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ASSISTANT PROFESSOR IN HUMAN-CENTERED COMPUTING

The Department of Computer Science at Virginia Tech (www.cs.vt.edu <http://www.cs.vt.edu/>) seeks applicants for a tenure-track assistant professor position in human-centered computing.  Exceptional candidates at higher ranks may also be considered. Strong candidates from any area related to human-computer interaction, user experience, or interactive computing are encouraged to apply. We especially encourage applicants with interests in novel interactive experiences and technologies—including immersive environments (virtual reality and augmented reality), multi-sensory displays, multi-modal input, visualization, visual analytics, human-robot interaction, game design, and creative technologies.

The successful candidate will have the opportunity to engage in transdisciplinary research, curriculum, and outreach initiatives with other university faculty working in the Creativity & Innovation (C&I) Strategic Growth Area, one of several new university-wide initiatives at Virginia Tech (see provost.vt.edu/destination-areas <http://provost.vt.edu/destination-areas>).  The C&I Strategic Growth Area is focused on empowering partners and stakeholders to collaborate on creativity, innovation, and entrepreneurship efforts that transcend disciplinary boundaries. Faculty working together in this area comprise a vibrant ecosystem that melds the exploration of innovative technologies and the design of creative experiences with best practices for developing impact-driven and meaningful outcomes and solutions.  Candidates with demonstrated experience in interdisciplinary teaching or research that aligns with the C&I vision (provost.vt.edu/destination-areas/sga-overview/sga-creativity.html <http://provost.vt.edu/destination-areas/sga-overview/sga-creativity.html>) are especially encouraged to apply. The successful candidate will also have opportunities for collaboration in the interdisciplinary Center for Human-Computer Interaction (www.hci.vt.edu <http://www.hci.vt.edu/>) that includes nearly 40 faculty across campus; the Institute for Creativity, Arts, and Technology (icat.vt.edu <http://icat.vt.edu/>) housed in the new Moss Arts Center; and the Discovery Analytics Center (dac.cs.vt.edu <http://dac.cs.vt.edu/>).

Applications must be submitted online to jobs.vt.edu <https://listings.jobs.vt.edu/postings/80519> for posting #TR0170152.  Applicant screening will begin on December 1, 2017 and continue until the position is filled. Inquiries should be directed to Dr. Doug Bowman, Search Committee Chair, dbowman@vt.edu <mailto:dbowman@vt.edu>.


--
Doug A. Bowman
Frank J. Maher Professor, Computer Science
Director, Center for Human-Computer Interaction
Fellow, Institute for Creativity, Arts, and Technology
Virginia Tech
dbowman@vt.edu
Personal: http://people.cs.vt.edu/~bowman/
Group: http://research.cs.vt.edu/3di/
Center: http://hci.vt.edu/
Twitter: @CHCI_VT

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Machine Learning Engineer, Speech Recognition 
 
Location: London, UK Contact: hello@ajalastudios.com 
 
Summary & Opportunity 
 
AJA.LA Studios is a funded early-stage startup developing speech and natural language understanding technologies for under-resourced languages. We are looking to hire an engineer, to be based in London, to participate in 

developing acoustic and 

language models, and related algorithms, for our suite of proprietary speech recognition products 

for a broad library of under-resourced languages. This role provides a unique opportunity to pursue research and 

commercialization of speech recognition

 for under-resourced languages. 
 
Ideally, candidates should be comfortable working with large quantities of data, have an interest 

in and/or demonstrate 

experience working with under-resourced languages, an interest in working on the entire R&D/product-development cycle. 
 
Skills & Requirements 
 
The ideal candidate should possess a combination of the following skills and qualifications 

•Masters or PhD in an analytical discipline through which you have acquired a strong knowledge of 

topics including 

o Theory and practice of speech recognition and/or speech processing (LSCVR) 

o Signal Processing/Pattern Recognition 

o Probability theory 

o Bayesian inference 

o Machine learning and related topics 

• Strong software development skills o Required: C/C++, Python, CUDA/Nsight IDE, shell scripting, Perl, Github/SVN 

o Optional/Additional: Java/Android/Gradle/Android Studio, Objective C/Xcode/Cocos2dx 

• Speech processing, Neural Network and Natural Language platforms and libraries 

o Kaldi, KenLM, OpenFST, and HTS 

o Theano, PDNN, pyTorch, TensorFlow 

• Operating Systems: Unix/Linux/Mac OS 
 
 
 
 

 1 The Green Richmond, TW9 1PL UK www.ajalastudios.com 

Salary 
 
We offer a compentitive salary, pension contribution, private medical insurance, and share options, flexible working hours, 

amongst other benefits. 

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Machine Learning Engineer, Speech Synthesis 
 
Location: London, UK Contact: hello@ajalastudios.com 
 
Summary & Opportunity 
 
AJA.LA Studios is a funded early-stage startup developing speech and natural language understanding technologies for under-resourced languages. We are looking to hire an engineer, to be based in London, to participate in developing unit-selection and parametric speech synthesis for a broad library of under-resourced languages. This role provides a unique opportunity to pursue research and commercialization of speech recognition for under-resourced languages. 
 
Ideally, candidates should be comfortable working with large quantities of data, have an interest in and/or demonstrate experience working with under-resourced languages, an interest in working on the entire R&D/product-development cycle, and possess the following skills and qualifications 
 
Skills & Requirements 
 
• Masters or PhD in an analytical discipline through which you have acquired a strong knowledge of 

topics including 

o Theory and practice of speech synthesis and/or speech processing, e.g. vocoding 

o Signal Processing/Pattern Recognition 

o Probability theory o Bayesian inference 

o Machine learning and related topics 

• Strong software development skills 

o Required: C/C++, Python, CUDA/Nsight IDE, shell scripting, Perl, Github/SVN 

o Optional/Additional: Java/Android/Gradle/Android Studio, Objective C/Xcode/Cocos2dx 

• Speech processing, Neural Network and Natural Language platforms and libraries 

o Festival, HTK, and HTS 

o Theano, PDNN, pyTorch, TensorFlow 

• Operating Systems: Unix/Linux/Mac OS 
 
 
 
 

 1 The Green Richmond, TW9 1PL UK 

www.ajalastudios.com 
Salary 
 
We offer a compentitive salary, pension contribution, private medical insurance, and share options, flexible working hours, 

amongst other benefits.

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One-year post-doctoral position in speech production, in the framework of the StopNCo ANR project (http://www.agence-nationale-recherche.fr/Project-ANR-14-CE30-0017 <http://www.agence-nationale-recherche.fr/Project-ANR-14-CE30-0017>), starting from March 2018  (at the latest in October 2018).
More details at: https://www.gipsa-lab.grenoble-inp.fr/~maeva.garnier/mes_documents/PostDocPosition-StopNCo.pdf
I would be thankful if you could circulate this job offer in your research institution and forward it to anyone who may be interested in.



Maëva Garnier

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Job Link: https://tinyurl.com/MINGLEPhD

PhD Position in Social Signal Processing for Multi-Sensor Conversation Quality Modeling

Location: Delft University of Technology, The Netherlands

Deadline: January 12 2018 (see below for application procedure)

Project Description:

An important but under-explored problem in computer science is the automated analysis of conversational dynamics in large unstructured social gatherings such as networking or mingling events. Research has shown that attending such events contributes greatly to career and personal success. While much progress has been made in the analysis of small pre-arranged conversations, scaling up robustly presents a number of fundamentally different challenges.

Unlike analysing small pre-arranged conversations, during mingling, sensor data is seriously contaminated. Moreover, determining who is talking with whom is difficult because groups can split and merge at will. A fundamentally different approach is needed to handle both the complexity of the social situation as well as the uncertainty of the sensor data when analysing such scenes.

The successful applicants will develop automated techniques to analyse multi-sensor data (video, acceleration, audio, etc) of human social behavior. They will work as part of a team on the NWO Funded Vidi project MINGLE (Modelling Group Dynamics in Complex Conversational Scenes from Non-Verbal Behaviour). They will have the opportunity to interact with researchers from both computer science and social science both locally and internationally.

The main aim of the project is to address the following question: How can multi-sensor processing and machine learning methods be developed to model the dynamics of conversational interaction in large social gatherings using only non-verbal behaviour? The two project advertised focus on developing novel computational methods to measure conversation quality (e.g. involvement, rapport) from multi-sensor streams in crowded environments

Job requirements:

We are looking students who have recently completed or expect very soon an MSc or equivalent degree in computer science, electrical/electronic engineering, applied mathematics, applied physics, or a related discipline. Experience in the following or related fields are preferred: signal/audio/speech processing, computer vision, machine learning, and pattern recognition. Some experience with embedded systems is a bonus, though not necessary.

The successful applicant will have:- good programming skills;- curiosity and analytical skills;- the ability to work in a multi-disciplinary team;- motivation to meet deadlines;- an affinity with the relevant social science research;- good oral and written communication skills;-proficiency in English;- an interest in communicating their research results to a wider audience;

Institution:

The department Intelligent Systems is part of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at Delft University of Technology. The faculty offers an internationally competitive interdisciplinary setting for its 500 employees, 350 PhD students and 1700 undergraduates. Together they work on a broad range of technical innovations in the fields of sustainable energy, quantum engineering, microelectronics, intelligent systems, software technology, and applied mathematics.???

The Pattern Recognition and BioInformatics Group is one of five groups in the department, consisting of 7 faculty and over 20 postdoc and PhD students. Within this group, research is carried out in three core subjects; pattern recognition, computer vision, and bioinformatics. One of the main focuses of the group is on developing tools and theories, and gaining knowledge and understanding applicable to a broad range of general problems but typically involving sensory data, e.g. times signals, images, video streams, or other physical measurement data.

For information about the TU Delft Graduate School, please visit www.phd.tudelft.nl.????

Application Procedure:

Interested applicants should send an up-to-date curriculum vitae, degree transcripts, letter of application, and the names and the contact information (telephone number and email address) of two references to Hr-eemcs@tudelft.nl with the subject heading '[MINGLE PhD]'.

The letter of application should summarise (i) why the applicant wants to do a PhD, (ii) why the project is of interest to the applicant, (iii) evidence of suitability for the job, and (iv) what the applicant hopes to gain from the position.

The application procedure is ongoing until the position is filled, so interested candidates are encouraged to apply as soon as possible and before January 12 2018. Note that candidates who apply after this deadline may still be considered but applications before the deadline will be given priority.

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L'équipe Expression de l'IRISA recrute un.e doctorant.e en
informatique sur le sujet 'caractérisation de registres de langue par
extraction de motifs séquentiels' dans le cadre du projet ANR TREMoLo.

Détails de l'offre :

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Adaptation des réseaux de neurones profonds pour les systèmes 

de transcription de la parole 
 
Mots-clés : système de transcription de la parole, modèle de langage, adaptation nonsupervisée 
 
Description La Reconnaissance Automatique de la Parole (RAP) consiste à transcrire en texte les mots 

prononcés dans un enregistrement audio ou vidéo. Les systèmes de RAP les plus robustes reposent 

souvent sur une architecture multi-passe (Gauvain et Lee 1994) (Gales 1998), 

chaque passe permettant d’obtenir une transcription du signal audio qui se veut de meilleure qualité 

que la précédente. 

Ainsi, dans certains cas, les sorties de la passe précédente sont utilisées pour adapter les modèles de la 

passe en cours. L’idée de cette adaptation est d’obtenir des modèles spécialisés à l’enregistrement, et 

donc d’être plus robuste face aux « variabilités » des enregistrements audio (conditions acoustiques différentes,

 locuteurs inconnus, spontanéité de la parole, bruits de l’environnement...). 
 
L’objectif général du stage est de faire progresser l’état de l’art sur la transcription automatique de la parole.  

Plus précisément, le stage explorera l’adaptation non-supervisée des réseaux de neurones profonds. 

Un des principaux challenges est d’utiliser les réseaux de neurones en tant que modèle de langage et de pouvoir 

les adapter à une première transcription issue du décodage. 
 
Ce sujet pourra donner lieu à une thèse. 
 
Profil du candidat Etudiant en Master 2 en informatique. Le candidat devra posséder un bon niveau en 

programmation (C/C++ et/ou Python). Des notions en Traitement Automatique de la Langue, Traitement de la parole 

ou Apprentissage automatique serait un plus. 
 
Lieu du stage LIA, 339, chemin des Meinajariès, 84911 Avignon 
 
Durée et rémunération 6 mois, environ 580€ par mois. 
 
Contact Mickaël Rouvier – Maître de conférence – mickael.rouvier@univ-avignon.fr Richard Dufour – Maître de conférence – richard.dufour@univ-avignon.fr 
 
Bibliographie Gales, Mark JF. «Maximum likelihood linear transformations for HMM-based speech recognition.» 

Computer Speech and Language (CSL), 1998. Gauvain, Jean-Luc, et Chin-Hui Lee. «Maximum 

a posteriori estimation for multivariate Gaussian mixture observations of Markov chains.» IEEE Transactions on 

Speech and Audio Processing (TASP), 1994. 

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Résumé vidéo automatique par contextualisation de vidéo à partir d’un texte 
 
 
Mots-clés : résumé automatique par extraction 
 
Description Le résumé automatique est un moyen de produire des synthèses qui extraient l’essentiel des contenus et 

les présentent de façon aussi concise que possible. Dans ce stage nous nous intéressons aux méthodes de résumé vidéo 

par extraction basées sur l’analyse du texte [Li11, Trione14, Favre15]. 
 
Une des approches classiques suivie pour la génération automatique de résumé vidéos consiste à passer par une 

représentation intermédiaire textuelle : le contenu audio de la vidéo (et parfois les textes incrustés) sont extraits, 

transcrits puis résumés. Ce résumé texte est ensuite utilisé pour assembler un résumé vidéo. L’objectif général du 

stage est d’explorer des méthodes de contextualisation de vidéos ou d’images à partir de la transcription texte. 

Cette contextualisation doit aider à la composition du résumé vidéo final. 
 
Ce sujet pourra donner lieu à une thèse. 
 
Profil du candidat Etudiant en Master 2 en informatique. Le candidat devra posséder un bon niveau en programmation 

(C/C++ et/ou Python). Des notions en Traitement Automatique de la Langue ou Apprentissage automatique seraient un plus. 
 
Lieu du stage LIA, 339, chemin des Meinajariès, 84911 Avignon 
 
Durée et rémunération 6 mois, environ 580€ par mois. 
 
Contact Mickaël Rouvier – Maître de conférence – mickael.rouvier@univ-avignon.fr Richard Dufour – Maître de conférence – richard.dufour@univ-avignon.fr 
 
Bibliographie [Li11] Li, Y., Merialdo, B., Rouvier, M., & Linares, G. (2011). Static and dynamic video summaries. In Proceedings 

of the 19th ACM international conference on Multimedia (pp. 1573-1576). ACM. 

[Trione14] Trione, J. (2014). Extraction methods for automatic summarization of spoken conversations from call centers 

(Méthodes par extraction pour le résumé automatique de conversations parlées provenant de centres d’appels)[in French]. In Proceedings of TALN 2014 (Volume 4: RECITAL-Student Research Workshop) (Vol. 4, pp. 104-111).

 [Favre15] Favre, B., Stepanov, E. A., Trione, J., Béchet, F., & Riccardi, G. (2015). Call Centre Conversation Summarization: 

A Pilot Task at Multiling 2015. In SIGDIAL Conference (pp. 232-236). 

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Internship and PhD position in machine learning for multimodal engagement analysis

in human-robot interactions (HRI)

Telecom ParisTech [1],  LTCI lab [2]

Duration:  6-month internship to be continued as 3-year PhD contract
Start: Any date from February 1st, 2018

Salary: according to background and experience

*Position description*

The internship/PhD project will take part in a collaboration between Softbank Robotics and Télécom ParisTech on the topic of engagement analysis in interactions of humans with Softbank?s robots.

The role of the intern/PhD student will consist in developing robust machine learning systems able to effectively take advantage of the multimodal signals acquired by the robot?s sensors during its interaction with a human. The work will include:

- the design of appropriate elicitation protocols and multimodal data acquisition procedures ;

- the development of multimodal feature learning and dynamic classification procedures capable of handling noisy observations with missing values, especially exploiting deep learning techniques ;

- the evaluation of the system in realistic scenarios involving end-users.

The PhD project will be hosted at Telecom ParisTech  department of images, data and signals of [3], jointly by the social computing [4] and the audio data analysis and signal processing [5] teams.

* Candidate profile*

As a minimum requirement, the successful candidate will have:

?    A Master?s degree (possibly to be granted in 2018) in one of the following areas: computer science, artificial intelligence, machine learning, signal processing, affective computing, applied mathematics

?    Excellent programming skills (preferably in Python)

?    Good command of English

The ideal candidate will also (optionally) have:

?    Knowledge in deep learning techniques

-- More about the position

?    Place of work: Paris, France

?    For more information about Télécom ParisTech see [1]

-- How to apply

Applications are to be sent to Chloé Clavel [6], Giovanna Varni [7] and Slim Essid [8] by email (using <firstname.lastname>@telecom-paristech.fr)

The application should be formatted as a single pdf file and should include:

?    A complete and detailed curriculum vitae

?    A letter of motivation

?    Academic records of the last two years

?    The names and addresses of two referees

[1] http://www.tsi.telecom-paristech.fr

[2] https://www.ltci.telecom-paristech.fr/?lang=en

[3] http://www.tsi.telecom-paristech.fr/en/

[4]https://www.tsi.telecom-paristech.fr/recherche/themes-de-recherche/analyse-automatique-des-donnees-sociales-social-computing/

[5] http://www.tsi.telecom-paristech.fr/aao/en/

[6] https://clavel.wp.mines-telecom.fr/

[7] http://sites.google.com/site/gvarnisite/

[8] http://www.telecom-paristech.fr/~essid

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L’Institut national de l’audiovisuel (INA), entreprise publique audiovisuelle et numérique, collecte, sauvegarde et transmet le patrimoine audiovisuel français. Dans une démarche d’innovation tournée vers les usages, l’INA valorise ses contenus et les partage avec le plus grand nombre : sur ina.fr pour le grand public, sur inamediapro.com pour les professionnels, à l’InaTHÈQUE pour les chercheurs. L’institut développe ainsi des offres et des services afin de se rapprocher de ses usagers et clients, en France comme à l’international. 

Son département Recherche et Innovation soutient une culture de l’innovation forte et ambitieuse. Notre technologie Ina-Signature (technologie de « fingerprint ») – issue de la R&D de l’Ina - a su s’imposer auprès de clients renommés, grâce à une stratégique axée sur la performance et la qualité. Notre offre continue à évoluer, avec la démocratisation du SAAS (software as a service) et du CLOUD. 

Dans le cadre de votre mission, rattaché/e au Chef du service de la Recherche, vous garantissez la conception, la mise en oeuvre, l'intégration ou l'adaptation des technologies d’apprentissage automatique, d’analyse et de fusion de données dans le cadre des projets de Recherche pour l’expérimentation de nouveaux usages de valorisation des contenus.

A ce titre, vous serez en charge de :

1 – Effectuer de la Recherche scientifique et technologique

-        Définir les axes de recherche et développement liés à cette thématique ;

-        Concevoir, implémenter, tester, évaluer des outils technologiques innovants dans le cadre des usages existants ou pressentis de l’Institut ;

-        Collaborer avec l’ensemble des acteurs internes et externes du département ;

-        Participer à la stratégie de recherche et développement du service ;

-        Encadrer des stagiaires et à terme des doctorants ;

-        Rédiger ou participer à la rédaction d’articles scientifiques et présenter ces articles dans des colloques ;

-        Démontrer les travaux de recherche lors de colloques, séminaire ou salons :

-        Participer à la rédaction des documents liés à l’activité (rapports d’activité, livrables des projets en particulier).

2 – Assurer une R&D au service de l’Institut

-        Proposer, préparer, coordonner, participer à des projets de Recherche et Développement internes en lien avec les services opérationnels ;

-        Proposer, piloter, participer à des actions de concertation et de réflexion internes et groupes de travail.

3 – Réaliser des partenariats

-        Proposer, préparer, coordonner, participer à des projets de Recherche et Développement collaboratifs, nationaux ou internationaux en lien avec des partenaires académiques, institutionnels ou industriels ;

-        Proposer, coordonner, participer à des instances de coopération scientifique et technologique (COMUE, Pôles de compétitivité, Groupes de recherche).

4 – Collaborer au management fonctionnel

-        Participer à la coordination du service (réunions de coordination) ;

-        Participer aux tâches de gestion des ressources informatiques et techniques du service ;

-        Participer à la vie du service (réunions de service, suivis d’activité, rapports).

Profil :

Vous justifierez d'un doctorat dans le domaine de l’apprentissage automatique et/ou de l’analyse de données ou d'un parcours professionnel admis en équivalence.

Complété de compétences en : 

-        Maîtrise et expérience dans le(s) domaine(s) suivants : apprentissage automatique (Deep Learning), analyse et fusion de données, analyse de l’image et/ou de l’audio, développement informatique

-        Bonne pratique en recherche académique et/ou industrielle ;

-        Pratique en publications scientifiques ;

-        Bonne connaissance et pratique de projets collaboratifs ;

-        Connaissance du paysage audiovisuel français ;

-        Connaissance du monde académique ;

-        Maîtrise des outils bureautiques ;

-        Intérêt pour le monde de l’audiovisuel et des médias ;

-        Intérêt pour les Sciences Humaines et Sociales et les Humanités Numériques

Des qualités d’analyse et de synthèse, de créativité et d’imagination, de force de proposition, relationnelles et d’esprit d’équipe seront vos meilleurs atouts pour réussir dans le poste.

Modalités du poste :

-        Contrat : CDI

-        Statut : Cadre

-        Poste à pourvoir : au plus vite

-        Salaire : selon expérience

-        Clôture de la consultation : 31 janvier 2018

-        Contact : jcarrive@ina.fr

-        Localisation géographique : Bry S/Marne (94)

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We are looking at the Uniklinik RWTH Aachen (Germany) for a postdoctoral researcher in
the field of articulatory modelling of the vocal tract for the analysis of dysarthria
from MRI images.

The position is for 14 months on the German pay scale TV-L 13 (typically around 2300? net
after all tax deduction) and expected to start around March 2018.

All details can be found here:
http://antoine.serrurier.free.fr/index_documents/2017_12_PostDoc_DysArtMod_EN.pdf

 

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===========================================
position 1:
===========================================
Name :    Multimodal people monitoring using sound (and vision)
Type :    Postdoc
Description :    The Idiap Research Institute together with Swiss Center for Electronics and Microtechnology (CSEM) invite applications for a post-doctoral position in research and development for multimodal people monitoring.
The position is funded for one year by Idiap (with a possible extension depending on his/her performance)

The successful candidate will work with Dr. Petr Motlicek in Idiap's Speech and Audio Processing group, engaged in world-class research in speech processing.
Exceptionally qualified candidate can also be considered for a longer-term Research Associate position.

Detailed description:
We have witnessed a large interest and potential of self-dependent smart sound devices to be deployed for security, surveillance, or emergency applications. Recent developments performed by CSEM in building occupancy detection and monitoring using embedded vision have led to the creation of successful monitoring applications. This project will focus on a combination of the visual and speech information which will take place in an embedded platform providing industrial grade vision sensing together with an acoustic front-end.

CSEM will provide an expertise in embedded platform, visual analysis and data fusion. The Idiap postdoctoral position will mainly focus on the speech related aspects of the project, including speaker identification and keyword spotting, aiming to operate with limited resources.

We envisage three related research threads for this position:
1. Parameter reduction, in which we will apply sparsity and relevance constraints to train neural networks that function using as few parameters as possible.
2. Acoustic modeling sharing between different applications, in which we will build on the commonality between technologies for automatic speech recognition or keyword spotting and speaker recognition to create a single system with multiple capabilities.
3. Far-field speech processing, in which we will process signals recorded by a microphone array to substantially increase SNR of the input signal.

The successful candidate will work at Idiap in Martigny, but in close collaboration with CSEM?s R&D team based in Switzerland.
The project is a unique combination of applied science and academic research expected to yield both reference designs and academic publications.

Profile:
Candidate should have either or both of:
1. A strong background in engineering, mathematics or a related discipline, along with the associated familiarity with modern distributed programming environments and languages such as C++, Python and Perl.
2. An exceptional academic record and a clear aptitude for creative (and independent) research in a related discipline.
In either case, familiarity with speech processing tools such as Kaldi and deep learning toolkits such as Torch will be a distinct advantage. Although a PhD is normally a prerequisite for a post-doctoral position, candidates without a PhD may be considered in exceptional cases.

Timescale:
The position is offered on a one-year basis with the possibility of renewal based on funding and performance.
The starting salary will be 80,000 CHF/year. Starting date could be immediate, but otherwise as soon as possible in 2018.


===========================================
position 2:
===========================================

Name :    Speech and Speaker recognition for HMI devices
Type :    Postdoc
Description :    The Idiap Research Institute together with a global industry partner, leader in Consumer Electronics, invite applications for two post-doctoral positions in speech and speaker recognition for HMI devices. The positions are funded for two years by the Swiss Commission for Technology and Innovation (CTI), enabling a collaboration between Idiap and an innovative product company.

The successful candidates will work with Dr. Philip N. Garner, and/or Dr. Petr Motlicek in Idiap's Speech and Audio Processing group, engaged in world-class research in speech processing. Exceptionally qualified candidates can also be considered for a longer-term Research Associate position.

Description

In recent years, the state of the art in speech and speaker recognition has been dominated by deep learning. Such technology is typically highly parametric; training can require significant CPU or GPU resources. The goal of the project is to investigate the application of the state of the art to the more limited resources of consumer-grade embedded systems which operate in combination with cloud services.

We envisage three related research threads:

1. Parameter reduction, in which we will apply sparsity and relevance constraints to train networks that function using as few parameters as possible.

2. Smart handover, in which we will assess the complexity of voice commands to optimise workload between local devices and cloud-based services.

3. System combination, in which we will build on the commonality between technologies for multilingual speech recognition, keyword spotting and speaker recognition to create a single system with multiple capabilities.

The successful candidates will work at Idiap in Martigny, but in close collaboration with the partner?s R&D team based in Switzerland. The project is a unique combination of applied science and academic research expected to yield both reference designs and academic publications.

Profile

Candidates should have either or both of:
1. A strong background in engineering, mathematics or a related discipline, along with the associated familiarity with modern distributed programming environments and languages such as C++, Python and Perl.
2. An exceptional academic record and a clear aptitude for creative (and independent) research in a related discipline.
In either case, familiarity with speech processing tools such as Kaldi and deep learning toolkits such as Torch will be a distinct advantage. Although a PhD is normally a prerequisite for a post-doctoral position, candidates without a PhD may be considered in exceptional cases.

Timescale

All positions are offered on a one-year basis with the possibility of renewal based on funding and performance. The starting salary will be 80,000 CHF/year. Starting date could be immediate, but otherwise as soon as possible in 2018.

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The Faculty of Information Technology (https://www.monash.edu/it) at Monash University in Melbourne Australia is establishing a new group in HCI and creative technologies. We invite accomplished and creative PhDs to apply for a 3-year postdoctoral fellowship in multimodal interfaces and behavior analytics. The selected candidate will join a rapidly expanding multidisciplinary group with expertise in areas such as mobile and multimodal-multisensor interfaces, agent-based conversational interfaces, brain-computer and adaptive interfaces, wearable and contextually-aware personalized interfaces, education and health interfaces, data analytics for predicting user cognition and health status, and other topics.

This position involves research on predicting user cognition and health status, based on analysis of different modalities (e.g., speech, writing, images, sensors) during naturally occurring activities. These analyses involve exploring predictive patterns at the signal, activity pattern, lexical, and/or transactional levels. The ideal candidate would be an initiating researcher with a strong publication record who is interested in pioneering in emerging research areas. He/she would have an interest in developing new technologies to identify users? cognitive and health status, and using this information to develop personalized and adaptive interfaces that promote learning, performance, and health.

Requirements:

?    PhD in computer science, engineering, information sciences, cognitive or linguistic sciences, or related field

?    Training in HCI, multimodal interfaces, data science and analytics, modeling human behavior & communication

?    Experience collecting and analyzing speech, images, handwriting, and/or other sensor data

?    Experience applying machine learning/deep learning, empirical/statistical, linguistic, or hybrid analysis methods

?    Interest in human cognition and educational technologies, and/or health and mental health technologies

?    Strong interpersonal, teamwork, communication and writing skills

?    Ability to work with diverse partners? domain experts (teachers, clinicians), industry, undergraduate/graduate students

?    Prefer candidate with 2-3 years post-PhD research or work experience            

HCI Group: The HCI group designs, builds, and evaluates state-of-the-art interface technologies. Our multidisciplinary interests span computer science and engineering, cognitive and learning sciences, communications, health, media design, and other topics. We are interested in applications such as health, education, communications, personal assistance, and digital arts. The HCI group has partnerships with CSIRO-Data61 and industry. The HCI area director is Dr. Sharon Oviatt, an ACM Fellow and international pioneer in human-centered, mobile, and multimodal interfaces (see https://www.monash.edu/it/our-research/graduate-research/scholarship-funded-phd-research-projects/projects/human-centred-mobile-and-multimodal-interfaces)

Monash is Australia?s largest university, and ranks in the top 60 universities worldwide, with Computer and Information Systems rated in the top 70 worldwide (QS World University rankings 2018). In addition to growing rapidly in human-centered computing, software, and cyber-security, it includes data science and machine learning, artificial intelligence and robotics, computational biology, social computing, and basic computer science.

Experimental Labs & Design Spaces: The university has made recent strategic investments in facilities for prototyping innovative concepts, collecting and analyzing data, and displaying digital installations and interactive media?including sensiLab (supporting tangible, wearable, augmented and virtual reality, multimodal-multimedia, maker-space), Immersive Visualization platform and Analytics lab, the Centre for Data Science, and the ARC Centre of Excellence on Integrative Brain function (pioneering new multimodal imaging techniques for data exploration). The university currently is investing in HCI group facilities for prototyping and developing new mobile, multimodal and multisensor interfaces, analyzing human multimodal interaction (e.g., whole-body activity, speech), and predicting users? cognitive and health status.

Melbourne Area: Melbourne recently has been rated the #1 city worldwide for quality of life (see Economist & Guardian, http://www.economist.com/blogs/graphicdetail/2016/08/daily-chart-14 and https://www.theguardian.com/australia-news/2016/aug/18/melbourne-wins-worlds-most-liveable-city-award-sixth-year-in-a-row), with excellent education, healthcare, infrastructure, low crime, and exceptional cuisine, cultural activities, and creative design. The regional area is renowned for its dramatic coastline, extensive parks, exotic wildlife, and Yarra Valley wine region.

Position & Compensation: This position is full-time for 3 years, with competitive salary (Academic level B-6, $119,683 AUD) and benefits, including 17% superannuation retirement fund, health insurance options, relocation, and seed funds for equipment and travel. Start date is negotiable after April 1, 2018. For enquiries, contact Oviatt@incaadesigns.org.

To apply: To submit an online application: http://careers.pageuppeople.com/513/cw/en/job/571150/research-fellow-multimodal-interfaces-behaviour-analytics  Required application materials include: (1) cover letter (indicating date of availability); (2) current CV with publication list, research and teaching interests, and 3 references with email/phone contact; (3) graduate transcripts; and (4) three representative publications. Monash has a Women in IT Program, and participates in the Athena Swan Charter to enhance gender equality. We welcome female, minority and international applicants.

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The Faculty of Information Technology (https://www.monash.edu/it) at Monash University in Melbourne Australia is establishing a new group in HCI and creative technologies, with openings for exceptionally accomplished, creative, and energetic faculty at all levels. Selected candidates will have the opportunity to join a rapidly growing group with expertise in state-of-the-art areas of human-centered computer interfaces. We are especially interested in adding faculty in these preferred areas:

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The Faculty of Information Technology (https://www.monash.edu/it) at Monash University in Melbourne Australia has two graduate scholarships for exceptionally initiating and talented students to pursue a PhD in HCI and creative technologies. The selected students will have the opportunity to join an expanding HCI group with expertise in state-of-the-art areas such as: human-centered interfaces, mobile and wearable interfaces, natural multimodal interfaces (speech, writing, images, touch), agent-based conversational interfaces, multimodal-multisensor interfaces, data analytics for predicting user cognition and health, and brain-computer and adaptive interfaces.

Successful PhD student applicants would conduct research on topics related to those outlined above in the HCI group. Most applicants would have a background in Computer and Information Systems, HCI, Interaction or Media Design, or a multidisciplinary topic related to their PhD interests such as Psychology, Cognitive Science, Neuroscience, Medicine and Health Sciences, Linguistics, or Engineering. Dr. Sharon Oviatt, director of the HCI area, will provide supervision. She is an internationally known pioneer in human-centered, mobile, and multimodal interfaces, and an ACM Fellow (see https://www.monash.edu/it/our-research/graduate-research/scholarship-funded-phd-research-projects/projects/human-centred-mobile-and-multimodal-interfaces)

HCI Group & University: The HCI group designs, builds, and evaluates state-of-the-art computer interface technologies. It has multidisciplinary interests spanning computer science and engineering, cognitive and learning sciences, communications, medicine and health, media design, and other topics. The group?s research is based on empirical science, statistics, deep learning and data analytics, and HCI methods. We are interested in applications in many areas, such as health, education, communications, personal assistance, robotics, automotive, and digital arts.

Monash is Australia?s largest university, and ranks in the top 60 universities worldwide, with Computer and Information Systems rated in the top 70 (QS World University rankings 2018). It is growing rapidly in human-centered interfaces, software, and cyber-security, but also includes data science and machine learning, artificial intelligence and robotics, computational biology, social computing, digital humanities, and traditional computer science.

Experimental Labs & Design Spaces: The university has made recent strategic investments in facilities for prototyping innovative concepts, collecting and analyzing data, and displaying digital installations and interactive media?including sensiLab (tangible, wearable, augmented and virtual reality, multimodal-multimedia, maker-space), Immersive Visualization platform and Analytics lab, the Centre for Data Science, and the ARC Centre of Excellence on Integrative Brain function (pioneering new multimodal imaging techniques for data exploration). The university currently is investing in HCI group facilities for prototyping and developing new mobile, multimodal, and multisensory interfaces, analyzing human multimodal interaction (e.g., whole-body activity, speech, writing), and predicting users? cognitive and health status.

Melbourne Area: Melbourne recently has been rated the #1 city worldwide for quality of life (see Economist & Guardian, http://www.economist.com/blogs/graphicdetail/2016/08/daily-chart-14 and https://www.theguardian.com/australia-news/2016/aug/18/melbourne-wins-worlds-most-liveable-city-award-sixth-year-in-a-row), with excellent education, healthcare, infrastructure, low crime, and exceptional cuisine, cultural activities, and creative design. The regional area is renowned for its dramatic coastline, extensive parks, exotic wildlife, and Yarra Valley wine region.

Scholarship Support: The funded PhD positions are for full-time study at the Monash Caufield campus in Melbourne, to begin during the 2018 academic year. They include $26,682 AUD scholarship (non-taxable), relocation allowance ($1,000), tuition waiver and Overseas Student Health Cover for international students. Full-time Monash Graduate Scholarships for PhD students are for 3 to 3.5 years. PhD students may be eligible for other Monash scholarships, or for supplements for data collection, publications, and conference travel. Monash has a Women in IT Program and scholarships for female students. We especially welcome female, minority and international applications. For further information, see https://www.monash.edu/__data/assets/pdf_file/0009/704763/2017-stipend-conditions-of-award-1.pdf and https://www.monash.edu/graduate-research/future-students/support, or email Dr. Sharon Oviatt (with ?PhD Student Application? in header) at:  Oviatt@incaadesigns.org

Scholarship Requirements: To be competitive, applicants should have first-class honors (H1), or the equivalent grade of 80% or above. Research experience and publications also are considered, so students with lower grades but strong evidence of research aptitude and experience are encouraged to apply.

To apply: For information about required application materials, and to submit an application online by the deadline, see https://www.monash.edu/graduate-research/future-students/apply and https://www.monash.edu/graduate-research/contact-us/faqs/how-to-apply. The academic term 1 begins in late February, and term 2 in late July. Graduate applications with scholarship support are due March 31 or August 31 for international students, and May 31 or Oct. 31 for domestic Australian students.

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We have a new opening for a post-doctoral researcher at Idiap Research Institute.  It is
a joint position with the Swiss Center for Electronics and Microtechnology (CSEM), and
involves investigation of deep learning in the context of speech and image processing.
For a full description, please see the link:
 http://www.idiap.ch/education-and-jobs/job-10236

Idiap is located in French speaking Switzerland, although the lab hosts many
nationalities, and functions in English.  All positions offer quite generous salaries.

Several similar positions at PhD, post-doc and senior level are available at the
institute in general.
 http://www.idiap.ch/en/join-us/job-opportunities

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(SENIOR) SPEECH SCIENTIST                                          
Voicebox is an acknowledged pioneer in the voice technology and application industry. Our patented innovations create compelling AI voice interfaces of unparalleled flexibility and usability in app dev. Trusted by many of the world’s leading companies, we have established a leadership position in the automotive market. And because our capabilities were developed against our vision of a single, unifying interface across all connected devices, our continued growth is being driven by new markets, such as connected TVs and mobile computing. Our ability to capture this growth requires that we continue to add to our diverse team of talented professionals. Our opportunity is your opportunity. 
As Speech Scientist you will work closely with the Cloud ASR team on cutting-edge conversational voice information retrieval systems.  Within this team of researchers and engineers you will improve existing products and develop brand new technologies. You will be responsible for the design, development and testing of large vocabulary speech application technologies and also engage in all aspects of research activities (e.g., writing proposals, conducting novel research, presenting and publishing your research results).
Typical work packages are: • Training and adaptation of acoustic models (car, mobile, far-field) for a multitude of languages • Develop statistical language models  for various applications and languages • Design and develop new speech applications • Tune and maintain speech applications • Adapt speech resources for certain customers’ requirements • Research, development and implementation of new algorithms in ASR. • Perform statistical analysis on large datasets (multiple terabytes of data)
Skills: • Highly independent and capable of fulfilling multiple project commitments concurrently • Passionate about analyzing data to solve problems and improve systems • Good analytical and diagnostic skills, quick learning • Coding skills in languages like in C/C++ or Java • Knowledge of multiple natural languages is a strong plus • Knowledge in digital signal processing • Be able to write technical specifications, requirements in English • Good English communication skills
Experience: • Prior experience training models for HMM/DNN-based recognizers (Kaldi/HTK) • Understanding of ASR training/decoding processes • Understanding of ASR front-end components • Knowhow of far-field and microphone array processing • Experience in UNIX environment, strong in scripting languages such as Bash, Perl and Python • Ph.D.  or Master in Computer Science, Electrical Engineering, Mathematics, or relevant field or strong professional experience.
 
VoiceBox Technologies Deutschland GmbH  Ramersdorfer Straße 1, 81669 München, Germany michaelw@voicebox.com

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Telecom ParisTech has three new permanent(indefinite tenure) faculty positions:

? Faculty position (Full Professor) in audio/speech/music signal processing
? Faculty position (Associate Professor) in deep learning applied to
temporal data analysis
? Faculty position (Associate Professor) in deep learning for image processing

More information on:
http://www.tsi.telecom-paristech.fr/en/blog/2018/01/05/three-new-permanent-tenure-faculty-positions/

Please note the following important dates:

? February 28th, 2018: closing date
? Mid-April 2018: hearings of preselected candidates (tentative dates
for hearings are April 11th and/or 13th)
? September 2018: tentative starting date

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Machine learning Software Engineer, Adobe Research - Speech Recognition
 
Description Creative Intelligence Lab within Adobe Research plays a key role in creating next-generation applications and features in Adobe’s flagship products, including Photoshop, Lightroom, Audition, and Acrobat. Creative Intelligence Lab is searching for a machine learning software engineer specializing in speech recognition. Responsibilities include working closely with researchers, engineers, user experience designers, and product managers to build prototypes that showcase new research technologies, and to help integrate those technologies into Adobe’s products. This position will initially focus on building a speech recognition system for our creative assistant, and may expand to include additional areas of innovation, such as text to speech, NLP, HCI, machine learning, and dialog systems. We’re looking for exceptional candidates with expertise in computer science or software engineering. For this position, we will give preference to candidates with experience in applied machine learning and speech recognition. For successful candidates, nearly all of the following will be true: You have significant experience in building robust, complex software systems. You are excellent at collaborating with a team to get work done. You are comfortable both building prototypes from scratch and writing maintainable code inside large existing codebases. You have shipped software in a commercial environment (start-ups a plus) and can deal with last-minute bug fixes and schedule changes. 
 
Requirements  M.S. degree or higher in Computer Science or a related field. Significant experience developing speech recognition systems (acoustic models, language models) using popular machine learning and deep learning software libraries, such as Kaldi and/or Tensorflow. Ability to write efficient, clean, and reusable code. Strong communication and collaboration skills. Ability and willingness to learn new technologies quickly. At Adobe, you will be immersed in an exceptional work environment that is recognized throughout the world on Best Companies lists. You will also be surrounded by colleagues who are committed to helping each other grow through our unique Check-In approach where ongoing feedback flows freely. If you’re looking to make an impact, Adobe's the place for you. Discover what our employees are saying about their career experiences on the Adobe Life blog and explore the meaningful benefits we offer. Adobe is an equal opportunity employer. We welcome and encourage diversity in the workplace regardless of race, gender, sexual orientation, gender identity, disability or veteran status.
 Contact: Trung Bui (bui@adobe.com) or Walter Chang (wachang@adobe.com)

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2018 PHD RESEARCH FELLOWSHIPS ( ML/Dialogue/Language/Speech)
Location: University of Trento , Italy

You may have enjoyed reading about bots, artificial intelligence, machine learning,
digital assistants, systems that support doctors, teachers, customers and help people.
Then, you would like to consider taking a front row seat and join the research team
that has been training intelligent machines and evaluating AI-based systems
for more than two decades, collaborating with best research labs in the world and
deployed them in the real-world.

Here is a sample of the projects ( http://sisl.disi.unitn.it/demo/ ) the Signals
and Interactive Systems Lab (University of Trento, Italy) has been leading:

-Natural Language Understanding systems for massive amount of human language data:
http://www.sensei-conversation.eu

-Amazon Alexa challenge on Conversational Systems:
http://sisl.disi.unitn.it/university-of-trento-is-selected-by-amazon-for-the-alexa-challenge/

-Designing AI personal agents for healthcare domain:
http://sisl.disi.unitn.it/pha/

We are looking for top-candidates for its funded PhD research fellowships.
Candidates should have background at least in one of the following areas:


- Speech Processing

- Natural Language Understanding

- Conversational Systems

- Machine Learning

Candidates will be working on research domains such as Conversational Agents,
Intelligent Systems, Speech/Text Document Mining and Summarization,
Human Behavior Understanding, Crowd Computing and AI-based systems for tutoring.


For more info on research and projects visit the lab website
Visit lab website at http://sisl.disi.unitn.it/

The SIS Lab research is driven by an interdisciplinary approach to research,
attracting researchers from  disciplines such as Digital Signal Processing,
Speech Processing, Computational Linguistics, Psychology, Neuroscience and
Machine Learning.

The  official language ( research and teaching ) of the department is English.

FELLOWSHIP

Gross amount of the fellowships ( internship and PhD ) is competitive and approximately
1.600 Euro/month.
Students may qualify for reduced campus lodging, transportation and cafeteria
reduced rates.

For more information about cost of living, campus, graduate education programs,
please visit the graduate school website at http://ict.unitn.it/

DEADLINES

Immediate openings with start date as early as March 2018.  Open until filled.

REQUIREMENTS

Strict requirement is at least Master level degree in Computer Science, Electrical
Engineering, Computational Linguistics or similar or affine disciplines. Students with
other background
(Physics, Applied Math) may apply as well. Background in at least one of the posted
research areas is required. All applicants should have good very programming, math skills
and used to team work.

HOW TO APPLY

Interested applicants should send their
1) CV
2) Statement of research interest and
3) three reference letters sent to:

Email: sisl-jobs@disi.unitn.it


For more info:

Signals and Interactive Systems Lab : http://sisl.disi.unitn.it/

PhD School : http://ict.unitn.it/

Department : http://disi.unitn.it/


Information Engineering and Computer Science Department (DISI)

DISI has a strong focus on cross-disciplinarity with professors from different
faculties of the University (Physical Science, Electrical Engineering, Economics,
Social Science, Cognitive Science, Computer Science) with international
background. DISI aims at exploiting the complementary experiences present in the
various research areas in order to develop innovative methods, technologies and
applications.

University of Trento

The University of Trento is consistently ranked as premiere Italian university
institution.
See http://www.unitn.it/en/node/1636/mid/2573

University of Trento is an equal opportunity employer.

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Post-doctoral researcher at Idiap Research  Institute. 

It is a joint position with the Swiss Center for Electronics and
Microtechnology (CSEM), and involves investigation of deep learning in the
context of speech and image processing.
For a full description, please see the link:
 http://www.idiap.ch/education-and-jobs/job-10236

Idiap is located in French speaking Switzerland, although the lab hosts many
nationalities, and functions in English.  All positions offer quite generous
salaries.

Several similar positions at PhD, post-doc and senior level are available at
the institute in general.
 http://www.idiap.ch/en/join-us/job-opportunities

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Post Doctoral Position (12 months)

Natural language processing: automatic speech recognition system using deep neural networks without out-of-vocabulary words

_______________________________________

- Location:INRIA Nancy Grand Est research center, France

- Research theme: PERCEPTION, COGNITION, INTERACTION

- Project-team: Multispeech

- Scientific Context:

More and more audio/video appear on Internet each day. About 300 hours of multimedia are uploaded per minute. In these multimedia sources, audio data represents a very important part. If these documents are not transcribed, automatic content retrieval is difficult or impossible. The classical approach for spoken content retrieval from audio documents is an automatic speech recognition followed by text retrieval.

An automatic speech recognition system (ASR) uses a lexicon containing the most frequent words of the language and only the words of the lexicon can be recognized by the system. New Proper Names (PNs) appear constantly, requiring dynamic updates of the lexicons used by the ASR. These PNs evolve over time and no vocabulary will ever contains all existing PNs. When a person searches for a document, proper names are used in the query. If these PNs have not been recognized, the document cannot be found. These missing PNs can be very important for the understanding of the document.

In this study, we will focus on the problem of proper names in automatic recognition systems. The problem is how to model relevant proper names for the audio document we want to transcribe.

- Missions:

We assume that in an audio document to transcribe we have missing proper names, i.e. proper names that are pronounced in the audio document but that are not in the lexicon of the automatic speech recognition system; these proper names cannot be recognized (out-of-vocabulary proper names, OOV PNs). The purpose of this work is to design a methodology how to find and model a list of relevant OOV PNs that correspond to an audio document.

Assuming that we have an approximate transcription of the audio document and huge text corpus extracted from internet, several methodologies could be studied:

• From the approximate OOV pronunciation in the transcription, generate the possible writings of the word (phoneme to character conversion) and search this word in the text corpus.

• A deep neural network can be designed to predict OOV proper names and their pronunciations with the training objective to maximize the retrieval of relevant OOV proper names.

The proposed approaches will be validated using the ASR developed in our team.

Keywords: deep neural networks, automatic speech recognition, lexicon, out-of-vocabulary words.

- Bibliography

[Mikolov2013] Mikolov, T., Chen, K., Corrado, G. and Dean, J. ?Efficient estimation of word representations in vector space?, Workshop at ICLR, 2013.

[Deng2013] Deng, L., Li, J., Huang, J.-T., Yao, K., Yu, D., Seide, F., Seltzer, M., Zweig, G., He, X., Williams, J., Gong, Y. and Acero A. ?Recent advances in deep learning for speech research at Microsoft?, Proceedings of ICASSP, 2013.

[Sheikh2016] Sheihk, I., Illina, I., Fohr, D., Linarès, G. ?Improved Neural Bag-of-Words Model to Retrieve Out-of-Vocabulary Words in Speech Recognition?. Interspeech, 2016.

[Li2017] J. Li, G. Ye, R. Zhao, J. Droppo, Y. Gong , ?Acoustic-to-Word Model without OOV?, ASRU, 2017.

- Skills and profile: PhD in computer science, background in statistics, natural language processing, experience with deep learning tools (keras, kaldi, etc.) and computer program skills (Perl, Python).

- Additional information:

Supervision and contact: Irina Illina, LORIA/INRIA (illina@loria.fr), Dominique Fohr INRIA/LORIA (dominique.fohr@loria.fr) https://members.loria.fr/IIllina/, https://members.loria.fr/DFohr/

Additional links : Ecole Doctorale IAEM Lorraine

Deadline to apply: June 6^th

Selection results: end of June

Duration :12 of months.

Starting date: between Nov. 1^st 2018 and Jan. 1^st 2019
Salary: about 2.115 euros net, medical insurance included

The candidates must have defended their PhD later than Sept. 1st 2016 and before the end of 2018. 

The candidates are required to provide the following documents in a single pdf or ZIP file: 

• CV including a description of your research activities (2 pages max) and a short description of what you consider to be your best contributions and why (1 page max and 3 contributions max); the contributions could be theoretical or  practical. Web links to the contributions should be provided. Include also a brief description of your scientific and career projects, and your scientific positioning regarding the proposed subject.

• The report(s) from your PhD external reviewer(s), if applicable.

• If you haven't defended yet, the list of expected members of your PhD committee (if known) and the expected date of defence.

In addition, at least one recommendation letter from the PhD advisor should be sent directly by their author(s) to the prospective postdoc advisor.

Help and benefits:

• Possibility of free French courses

• Help for finding housing

• Help for the resident card procedure and for husband/wife visa

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Natural language processing: adding new words to a speech recognition system using Deep Neural Networks

- Location: INRIA/LORIA Nancy Grand Est research center France

- Research theme:Perception, Cognition, Interaction

- Project-team: Multispeech

- Scientific Context:

Voice is seen as the next big field for computer interaction. The research company Gartner reckons that by 2018, 30% of all interactions with devices will be voice-based: people can speak up to four times faster than they can type, and the technology behind voice interaction is improving all the time.

As of October 2017, Amazon Echo is present in about 4% of American households. Voice assistants are proliferating in smartphones too: Apple?s Siri handles over 2 billion commands a week, and 20% of Google searches on Android-powered handsets in America are done by voice input.

The proper nouns (PNs) play a particular role: they are often important to understand a message and can vary enormously. For example, a voice assistant should know the names of all your friends; a search engine should know the names of all famous people and places, names of museums, etc.

An automatic speech recognition system uses a lexicon containing the most frequent words of the language and only the words of the lexicon can be recognized by the system. It is impossible to add all possible proper names because there are millions proper names and new ones appear every day. A competitive solution is to dynamically add new PNs into the ASR system. The idea is to add only relevant proper names: for instance if we want to transcribe a video document about football results, we should add the names of famous football players and not politicians.

In this study, we will focus on the problem of proper names in automatic recognition systems. The problem is to find relevant proper names for the audio document we want to transcribe. To select the relevant proper names, we propose to use an artificial neural network.

- Missions:

We assume that in an audio document to transcribe we have missing proper names, i.e. proper names that are pronounced in the audio document but that are not in the lexicon of the automatic speech recognition system; these proper names cannot be recognized (out-of-vocabulary proper names, OOV PNs)

The goal of this PhDThesis is to find a list of relevant OOV PNs that correspond to an audio document and to integrate them in the speech recognition system. We will use a Deep neural network to find relevant OOV PNs The input of the DNN will be the approximate transcription of the audio document and the output will be the list of relevant OOV PNs with their probabilities. The retrieved proper names will be added to the lexicon and a new recognition of the audio document will be performed.

During the thesis, the student will investigate methodologies based on deep neural networks [Deng2013]. The candidate will study different structures of DNN and different representation of documents [Mikolov2013]. The student will validate the proposed approaches using the automatic transcription system of radio broadcast developed in our team.

- Bibliography:

[Mikolov2013] Mikolov, T., Chen, K., Corrado, G. and Dean, J. ?Efficient estimation of word representations in vector space?, Workshop at ICLR, 2013.

[Deng2013] Deng, L., Li, J., Huang, J.-T., Yao, K., Yu, D., Seide, F., Seltzer, M., Zweig, G., He, X., Williams, J., Gong, Y. and Acero A. ?Recent advances in deep learning for speech research at Microsoft?, Proceedings of ICASSP, 2013.

[Sheikh2016] Sheihk, I., Illina, I., Fohr, D., Linarès, G. ?Improved Neural Bag-of-Words Model to Retrieve Out-of-Vocabulary Words in Speech Recognition?. Interspeech, 2016.

- Skills and profile: Master in computer science, background in statistics, natural language processing, experience with deep learning tools (keras, kaldi, etc.) and computer program skills (Perl, Python).

- Additional information:

Supervision and contact: Irina Illina, LORIA/INRIA (illina@loria.fr), Dominique Fohr INRIA/LORIA (dominique.fohr@loria.fr) https://members.loria.fr/IIllina/, https://members.loria.fr/DFohr/

Additional links: Ecole Doctorale IAEM Lorraine

Duration: 3 years

Starting date: between Oct. 1st 2018 and Jan. 1st 2019

Deadline to apply : May 1^st 2018

The candidates are required to provide the following documents in a single pdf or ZIP file: 

• CV

• A cover/motivation letter describing their interest in the topic 

• Degree certificates and transcripts for Bachelor and Master (or the last 5 years)

• Master thesis (or equivalent) if it is already completed, or a description of the work in progress, otherwise

• The publications (or web links) of the candidate, if any (it is not expected that they have any)

In addition, one recommendation letter from the person who supervises(d) the Master thesis (or research project or internship) should be sent directly by his/her author to the prospective PhD advisor.

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Junior Linguist [French]

Job Title:

Junior Linguist [French]

Linguistic Field(s):

Phonetics, Phonology, Morphology, Semantics, Syntax, Lexicography, NLP

Location:

Paris, France

Job description:

The role of the Junior Linguist is to annotate and review linguistic data in French. The Junior Linguist will also contribute to a number of other tasks to improve natural language processing. The tasks include:

• Providing phonetic/phonemic transcription of lexicon entries

• Analyzing acoustic data to evaluate speech synthesis

• Annotating and reviewing linguistic data

• Labeling text for disambiguation, expansion, and text normalization

• Annotating lexicon entries according to guidelines

• Evaluating current system outputs

• Deriving NLP data for new and on-going projects

• Be able to work independently with confidence and little oversight

Minimum Requirements:

• Native speaker of French and fluent in English

• Extensive knowledge of phonetic/phonemic transcriptions

• Familiarity with TTS tools and techniques

• Experience in annotation work

• Knowledge of phonetics, phonology, semantics, syntax, morphology or lexicography

• Excellent oral and written communication skills

• Attention to detail and good organizational skills

Desired Skills:

• Degree in Linguistics or Computational Linguistics or Speech processing

• Ability to quickly grasp technical concepts; learn in-house tools

• Keen interest in technology and computer-literate

• Listening Skills

• Fast and Accurate Keyboard Typing Skills

• Familiarity with Transcription Software

• Editing, Grammar Check and Proofing Skills

• Research Skills

CV + motivation letter : maroussia.houimli@adeccooutsourcing.fr

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