Master2 position at Multispeech Team, LORIA (Nancy, France)

Automatic speech recognition: contextualisation of the language model based on neural networks by dynamic adjustment

Framework of ANR project ContNomina

The technologies involved in information retrieval in large audio/video databases are often based on the analysis of large, but closed, corpora, and on machine learning techniques and statistical modeling of the written and spoken language. The effectiveness of these approaches is now widely acknowledged, but they nevertheless have major flaws, particularly for what concern proper names, that are crucial for the interpretation of the content.

In the context of diachronic data (data which change over time) new proper names appear constantly requiring dynamic updates of the lexicons and language models used by the speech recognition system.

As a result, the ANR project ContNomina (2013-2017) focuses on the problem of proper names in automatic audio processing systems by exploiting in the most efficient way the context of the processed documents. To do this, the student will address the contextualization of the recognition module through the dynamic adjustment of the language model in order to make it more accurate.

Subject

Current systems for automatic speech recognition are based on statistical approaches. They require three components: an acoustic model, a lexicon and a language model. This stage will focus on the language model. The language model of our recognition system is based on a neural network learned from a large corpus of text. The problem is to re-estimate the language model parameters for a new proper name depending on its context and a small amount of adaptation data. Several tracks can be explored: adapting the language model, using a class model or studying the notion of analogy.

Our team has developed a fully automatic system for speech recognition to transcribe a radio broadcast from the corresponding audio file. The student will develop a new module whose function is to integrate new proper names in the language model.

Required skills

Background in statistics and object-oriented programming.

Localization and contacts

Loria laboratory, Multispeech team, Nancy, France

Irina.illina@loria.frdominique.fohr@loria.fr

Candidates should email a detailed CV and diploma

References

[1] J. Gao, X. He, L. Deng Deep Learning for Web Search and Natural Language Processing , Microsoft slides, 2015

[2] X. Liu, Y. Wang, X. Chen, M. J. F. Gales, and P. C. Woodland. Efficient lattice rescoring using recurrent neural network langage models, in Proc. ICASSP, 2014, pp. 4941?4945.

[3] M. Sundermeyer, H. Ney, and R. Schlüter. From Feedforward to Recurrent LSTM Neural Networks for Language Modeling. IEEE/ACM Transactions on Audio, Speech, and Language Processing, volume 23, number 3, pages 517-529, March 2015.

Top

The Idiap Research Institute (http://www.idiap.ch  ) seeks qualified candidates for one
PostDoc position in the field of automatic speaker recognition (ASR) .

The research will be conducted in the framework of the SNSF funded project ODESSA (Online
Diarization Enhanced by recent Speaker identification and Structured prediction
Approaches) in partnership with LIMSI and EURECOM in France.

Broadly, the goal of an automatic speaker recognition system is to authenticate or to
identify a person through speech signal.
Speaker diarization is an unsupervised process that aims at identifying each speaker
within an audio stream and determining the intervals during which each speaker is active.

The overall goal of the position is to advance the state-of-the-art in speaker
recognition and diarization. Specifically, the research will:
* investigate i-vectors and deep neural network for ASR and their application to the
problem of speaker diarization,
* explore the use of domain adaptation.

The proposed research is a collaboration between LIMSI (Hervé Bredin, Claude Barras),
EURECOM (Nicholas Evans) and the Biometrics group (Dr. Sebastien
Marcel,http://www.idiap.ch/~marcel  ) at Idiap.
The research will rely on previous knowledge and softwares developed at Idiap, more
specifically Bob toolkit (http://idiap.github.io/bob/  ) and Spear
(https://pypi.python.org/pypi/bob.spear  ). In addition the use
of additional libraries for deep learning (Torch, Caffe or Theano) are considered.

Reproducible research is a cornerstone of the project. Hence a strong involvement in data
collection and open source libraries such as Bob and Spear are expected.

The ideal candidate should hold a PhD degree in computer science, electrical engineering
or related fields. She or he should have a background in statistics or applied
mathematics, optimization, linear algebra and signal processing. The applicant should
also have strong programming skills and be familiar with Python, C/C++ (MATLAB is not a
plus), various scripting languages and with the Linux environment. Knowledge in speech
processing and machine learning is an asset. Shortlisted candidate may undergo a series
of tests including technical reading and writing in English and programming (in Python
and/or C/C++).

Appointment for the position is for 3 years, provided successful progress and may be
renewed depending on funding opportunities. Salary on the first year starts at 80'000 CHF
(gross salary). Starting date is early 2016.

Apply online
here:http://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710179%27%7D

Top

Ph.D. Position in Speech Recognition at Saarland University

The spoken Language Systems group from Saarland University in Germany anticipates the availability of a Ph.D. position in the area of speech recognition. This position is part of the Horizon 2020 project MALORCA, a research project on long term unsupervised adaptation of the acoustic and the language models of a speech recognition system. The research will be carried out together with a European consortium of high-profile research institutes and companies.

Requirements:

• Degree in computer science, electrical engineering or a discipline with a related background.

• Excellent programming skills C/C++, python and/or perl.

• Experience with Linux and bash-scripting.

• Very good math background.

• Very good oral and written English communication skills.

• Interest in speech recognition research.

Salary:

• The position is fully funded with a salary in the range of 45,000 Euros to 55,000 Euros per year depending on the qualification and professional experience of the successful candidate.

• The position is full time, for two years (with possibility of extension).

• Starting date is April 1st 2016.

Research at Saarland University:

Saarland University is one of the leading European research sites in computational linguistics and offers an active, stimulating research environment. Close working relationships are maintained between the Departments of Computational Linguistics and Computer Science. Both are part of the Cluster of Excellence, which also includes the Max Planck Institutes for Informatics (MPI-INF) and Software Systems (MPI-SWS) and the German Research Center for Artificial Intelligence (DFKI).

Each application should include:

Curriculum Vitae including a list of relevant research experience in addition to a list of publications (if applies).

• Transcript of records BSc/MSc.

• Statement of interest (letter of motivation).

• Names of two references.

• Any other supporting information or documents.

Applications (documents in PDF format in a single file) should be sent no later than, Sunday, January 10th to: sekretariat@LSV.Uni-Saarland.De

Further inquiries regarding the project should be directed to:

Youssef.Oualil@LSV.Uni-Saarland.De

or

Dietrich.Klakow@LSV.Uni-Saarland.De

Top

PostDoc Position in Speech Recognition at Saarland University

The spoken Language Systems group from Saarland University in Germany anticipates the availability of a PostDoc position in the area of speech recognition. This position is part of the Horizon 2020 project MALORCA, a research project on long term unsupervised adaptation of the acoustic and the language models of a speech recognition system. The research will be carried out together with a European consortium of high-profile research institutes and companies.

Requirements:

• Degree in computer science, electrical engineering or a discipline with a related background.

• Excellent programming skills C/C++, python and/or perl.

• Experience with Linux and bash-scripting.

• Very good math background.

• Very good oral and written English communication skills.

• Interest in speech recognition research.

Salary:

• The position is fully funded with a salary in the range of 45,000 Euros to 55,000 Euros per year depending on the qualification and professional experience of the successful candidate.

• The position is full time, for two years.

• Starting date is April 1st 2016.

Research at Saarland University:

Saarland University is one of the leading European research sites in computational linguistics and offers an active, stimulating research environment. Close working relationships are maintained between the Departments of Computational Linguistics and Computer Science. Both are part of the Cluster of Excellence, which also includes the Max Planck Institutes for Informatics (MPI-INF) and Software Systems (MPI-SWS) and the German Research Center for Artificial Intelligence (DFKI).

Each application should include:

Curriculum Vitae including a list of relevant research experience in addition to a list of publications (if applies).

• Transcript of records BSc/MSc (Ph.D. if applies).

• Statement of interest (letter of motivation).

• Names of two references.

• Any other supporting information or documents.

Applications (documents in PDF format in a single file) should be sent no later than, Sunday, January 10th to: sekretariat@LSV.Uni-Saarland.De

Further inquiries regarding the project should be directed to:

Youssef.Oualil@LSV.Uni-Saarland.De

or

Dietrich.Klakow@LSV.Uni-Saarland.De

Top

School of Linguistic, Speech and Communication Sciences

Ussher Assistant Professor in Irish Speech and Language Technology

The Ussher Assistant Professor in Irish Speech and Language Technology in the School of Linguistic, Speech and Communication Sciences will lead the development of the Irish Speech and Language Technology Research Centre (ITUT). This research will embed innovative speech and language technology resources in pedagogically sound language learning applications and in assistive technologies, enhancing teaching and learning of Irish nationally and globally. The appointee will have a strong background in speech-language technology, a specialisation in technology-assisted language learning, and a track record in linguistics research. Outreach and dissemination are key features of this post. The appointee will contribute to teaching and research supervision. A high level of competence in Irish language is desirable.

Appointment will be made at a maximum of the 8^th point of the New Assistant Professor Merged Salary Scale.

Candidates wishing to discuss the post informally should contact:

Professor Elaine Uí Dhonnchadha, E-mail: uidhonne@tcd.ie

Applications will only be accepted through e-recruitment

Further information and application details can be found at: https://jobs.tcd.ie

Closing date for receipt of completed applications is: no later than 12 Noon GMT on Thursday 14^th January 2016

Top

Sujet de stage Master

« Synchronisation automatique de sous-titrages pour le spectacle vivant »

Encadrant : Jean-François Bonastre (jean-francois.bonastre@univ-avignon.fr)

Ce stage a pour objet de réaliser une étude de faisabilité pour un dispositif de

synchronisation automatique de sous-titrages pour le spectacle vivant et, plus

particulièrement, pour le théâtre.

Les textes intégraux initiaux correspondant à la pièce jouée sont ramenés à des

sous-titres de longueur plus réduite, pour permettre un affichage et une lecture en

temps réel sur une tablette ou des lunettes de réalité virtuelle. Plusieurs versions

des sous-titres sont réalisées dans plusieurs langues. Ces sous-titres sont

manuellement synchronisés avec le texte de référence.

L’objectif principal visé par le projet est de permettre aux théâtres français de

pouvoir proposer leurs programmations à des publics non francophones et

d’ouvrir ainsi l’ensemble du répertoire théâtral en langue française aux 80 millions

de visiteurs étrangers qui viennent chaque année en France.

Le travail demandé consiste à réaliser une maquette fonctionnelle de l’application

de synchronisation automatique. Basée sur la plateforme ALIZE de

reconnaissance du locuteur, cette application cherchera à reconnaitre en temps

réel l’acteur en train de parler et utilisera la succession des prises de parole pour

synchroniser le live avec les sous-titres. L’application sera développée en C++ et

en python.

Des compétences solides en développement logiciel sont demandées. Des

connaissances en traitement automatique de la parole, en traitement du signal et

en apprentissage automatique sont également souhaitées, sans que cette liste

soit impérative ou exclusive.

Ce projet est présenté en partenariat étroit avec un centre spécialisé dans les

applications numériques pour le monde du théâtre. Ce partenaire apportera ses

compétences, les données servant à réaliser et à évaluer la maquette ainsi que

les théâtres partenaires (déjà identifiés) volontaires pour tester l’application « in

situ ». Une poursuite en thèse de Doctorat est souhaitée.

Le stage est prévu pour le premier semestre 2016.

Top

Faculty position at the Associate,Professor level in machine learning
applied to temporal data analysis.
Telecom ParisTech [1], CNRS - LTCI lab [2]

-- Important Dates (tentative)
?    February 15th, 2016: closing date
?    End of March: hearings of preselected candidates


Applications are invited for a permanent (indefinite tenure) faculty
position at the Associate
Professor level (Maitre de Conferences) in machine learning applied to
temporal data analysis.

-- Main missions

The hired associate professor will be expected to:

Research activities
?    Develop research in machine learning applied to temporal data
analysis that fits with the
topics of the Audio, Acoustics and Waves (AAO) group [3] and the Image
and Signal Processing
department [4], which include (and is not restricted to) audio,
physiological or video data analysis?
?    Develop both academic and industrial collaborations on the previous
topic, including
collaborative activities with other Telecom ParisTech research
departments and teams, and research
contracts with industrial players
?    Submit proposals to national and international research project calls

Teaching activities
?    Participate in teaching activities at Telecom ParisTech and its
partners (as part of joint
Master programs), especially in machine learning and signal processing,
including life-long training
programs (e.g. the local Data Scientist certificate)

Impact
?    Publish high quality research work in leading journals and conferences
?    Be an active member of the research community (serving in
scientific committees and boards,
organizing seminars, workshops, special sessions...)


-- Candidate profile

As a minimum requirement, the successful candidate will have:

?    A PhD degree
?    A track record of research and publication in one or more of the
following areas: machine
learning, signal processing
?    Experience in temporal data analysis problems (sequence prediction,
multivariate time series,
probabilistic graphical models, recurrent neural networks...)
?    Experience in teaching
?    Good command of English

The ideal candidate will also (optionally) have:
?    Knowledge in deep learning methods
?    Experience in distributed computing environments

Other skills expected include:
?    Capacity to work in a team and develop good relationships
withcolleagues and peers
?    Good writing and pedagogical skills

-- More about the position
?    Place of work: Paris until 2019, then Saclay (Paris outskirts)
?    For more information about being an Associate Professor at Telecom
ParisTech (in French), check [5]

-- How to apply
Applications are to be sent by e-mail to: recrutement@telecom-paristech.fr

The application should include:
?    A complete and detailed curriculum vitae
?    A letter of motivation
?    A document detailing past activities of the candidate in teaching
and research: the two types
of activities will be described with the same level of detail and rigor.
?    The texts of the main publications
?    The names and addresses of two referees
?    A short teaching project and a research project (maximum 3 pages)


-- Contact :
Slim Essid (Head of the AAO group)
Gaël Richard (Head of the TSI department)



[1] http://www.tsi.telecom-paristech.fr
[2] https://www.ltci.telecom-paristech.fr/?lang=en
[3] http://www.tsi.telecom-paristech.fr/aao/en/
[4] http://www.tsi.telecom-paristech.fr/en/
[5]
http://www.telecom-paristech.fr/telecom-paristech/offres-emploi-stages-theses/recrute-enseignants-chercheurs.html

Top

Job Overview

JOB TITLE: GENERAL EDUCATION INSTRUCTORS/Speech Communications

JOB TYPE: Part-Time

LOCATION: US-SC-COLUMBIA

DEPARTMENT: Academics

SUPERVISORY: No

TRAVEL REQ’D: No

Job Description

If you’re a dedicated, enthusiastic, experienced speech communications professional, preferably with teaching experience, who believes in the power of sharing your knowledge, motivating others, and putting students first, we want to hear from you!

We’re looking for talented general education instructors to join the academic team at our Columbia Campus for our day and evening class sessions. These individuals will report to the Campus’s Degree Program Department Chairperson.

Essential Duties/Responsibilities:

 Educates and trains students in his or her field of expertise using accepted and approved instructional methodology.

 Prepares lesson plans using industry-standard approaches (e.g., multimedia, adult learning methodology).

 Teaches courses as assigned, instructs and evaluates students, develops students’ skills and encourages growth, and tracks their attendance, performance, and grades.

 Participates in various administrative activities (e.g., attends faculty/staff meetings or in-service meetings).

 Participates in graduation ceremonies, as assigned.

 Participates regularly in continuing professional development activities.

 Performs other duties or special projects as assigned.

Education/Experience Needed:

 A related master's degree from a regionally accredited institution, with 18 or more graduate hours in speech, speech communications, or mass communications.

 A minimum of four (4) years of experience in a related field.

 Registration, license, or certification as required by the state or accrediting agencies.

 Excellent interpersonal, organizational, and communications skills a must.

 Computer literacy and teaching experience desired.

Learn more about us at Remington College – Columbia Campus.

We offer a competitive salary, along with a comprehensive benefits package that includes health, dental, disability, life, vision, 401K, and flexible spending accounts, for full-time employees.

How to Apply

Help us train tomorrow’s work force! Qualified candidates: Please click the APPLY NOW button. Or, you may email your résumé and cover letter for consideration to audrey.breland@remingtoncollege.edu.

We provide reasonable accommodation where appropriate to applicants with disabilities.

Top

POST-DOC OPENING
IN SPEECH INTELLIGIBILITY AT IRIT-TOULOUSE, FRANCE

****************************************************************

Title: Postdoctoral position in speech intelligibility

Application deadline: 1/31/2016

Description: The decreasing mortality of Head and Neck Cancers highlights the importance to reduce the impact on Quality of Life (QoL). But, the usual tools for assessing QoL are not relevant for measuring the impact of the treatment on the main functions involved by the sequelae. Validated tools for measuring the functional outcomes of carcinologic treatment are missing, in particular for speech disorders. Some assessments are available for voice disorders in laryngeal cancer but there are based on very poor tools for oral and pharyngeal cancers involving more the articulation of speech than voice.

In this context, the C2SI (Carcinologic Speech Severity Index) project proposes to develop a severity index of speech disorders describing the outcomes of therapeutic protocols completing the survival rates. There is a strong collaboration between linguists, phoneticians, speech therapists and computer science researchers, in particular those from the Toulouse Institute of Computer Science Research (IRIT), within the SAMoVA team (http://www.irit.fr/recherches/SAMOVA/).

Intelligibility of speech is the usual way to quantify the severity of neurologic speech disorders. But this measure is not valid in clinical practice because of several difficulties as the familiarity effect of this kind of speech and the poor inter-judge reproducibility. Moreover, the transcription intelligibility scores do not accurately reflect listener comprehension. Therefore, our hypothesis is that an automatic assessment technic can measure the impact of the speech disorders on the communication abilities giving a severity index of speech in patients treated for head and neck and particularly for oral and pharyngeal cancer.

The main objective is then to demonstrate that the C2SI, obtained by an automatic speech processing tool, produces equivalent or superior outcomes than a score of speech intelligibility obtained by human listeners, in terms of QoL foreseeing the speech handicap, after the treatment of oral and/or pharyngeal cancer. 

The database is actually recorded at the Institut Universitaire du Cancer in Toulouse with CVC pseudo-words, readings, short sentences focusing on prosody and spontaneous descriptions of pictures. 

Roadmap to develop an automatic system that will evaluate the intelligibility of impaired speech:

- Study existing SAMoVA technologies and evaluate them with the C2SI protocol,

- Find relevant features with the audio signal that support intelligibility,

- Merge those features to obtain the C2SI,

- Correlate it with the speech intelligibility scores obtained by human listeners,

- Study in which way the features support understandability as well.

Skills:

For this project, we are looking for one candidate with a PhD degree in the areas of machine learning, signal processing, and also with: programming skills, scientific rigour, creativity, good publication record, excellent communication skills, enjoying teamwork...

Salary and other conditions of employments will follow CNRS (French National Center for Scientific Research) standard rules for non-permanent researchers, according to the experience of the candidate.

Location: the work will be conducted in the SAMoVA team of the IRIT, Toulouse (France).

Contact: Jérôme Farinas jerome.farinas@irit.fr , Julie Mauclair julie.mauclair@irit.fr

Duration: 12 to 24 months

Candidates should email a letter of application, a detailed CV including a complete list of publications, and source code showcasing programming skills if available.

Top

LIMSI (www.limsi.fr) is looking for a software/research engineer to work on the
design and development of new features for the CAMOMILE platform.

The CAMOMILE platform provides a REST API backend to support collaborative
annotation of multimedia documents. It has been successfully used for the
organization in 2015 of the MediaEval 'Person Discovery' challenge [1].

Features that need to be improved or added to the CAMOMILE platform includes:
- user authentication (currently based on cookies)
- real-time collaboration (e.g. using socket.io)
- metadata validation (e.g. using ValidateJS)
- interface between CAMOMILE and Amazon Mechanical Turk crowd-sourcing platform

This list is not exhaustive and the candidates is expected to be pro-active
in the choice of new features to implement and of the selected technology.

Applicants should be experienced in Node.js + MongoDB architecture. Python
proficiency is an asset as both Javascript and Python clients will need to be
kept synchronized with the CAMOMILE REST API.

The engineer will also support the organization of the 2016 edition of the
MediaEval 'Person Discovery' challenge, in particular through the design of
web front-end for registration, leaderboard, collaborative annotation of video
segments (see [1] for more details).

Candidates should send CV and motivation letter.
For more details on the position, please contact us.

Employer: Centre National de la Recherche Scientifique
Location: Orsay, France
Contract: 6 to 12 months contract (CDD), starting as soon as possible
Salary: between 24 k? and 35 k? gross yearly salary, depending on diplomas and experience
Contact: Hervé Bredin, bredin@limsi.fr

[1] https://github.com/camomile-project/LREC2016/blob/master/abstract.md


Hervé Bredin
Researcher
LIMSI, CNRS
bredin@limsi.fr

Top

 *Institut national de l?audiovisuel*

Département recherche

Groupe de recherches audiovisuelles

Contact : Jean Carrive (jcarrive@ina.fr <mailto:jcarrive@ina.fr&gt;)

*Recrutement*

*Ingénieur R&D en CDI pour le département de la recherche de l?Ina*

*Analyse de l?audio et de la parole//*


  Missions

Dans le cadre des projets du Département de la recherche et dans le
cadre de projets transverses impliquant le Département, l?Ina recrute
un(e) ingénieur(e) Recherche et Développement chargé(e) de la mise en
?uvre, de l?intégration ou de l?adaptation de technologies d?analyse
automatique de contenus audiovisuels, et plus particulièrement de
technologies de traitement de la parole et d'analyse de l'audio.

Il/elle sera en particulier en charge de poursuivre les travaux déjà
initiés sur la reconnaissance et l'indexation des locuteurs (voir le
démonstrateur « SpeechTrax » en ligne sur l'Espace Recherche
http://recherche.ina.fr ainsi que les publications scientifiques
correspondantes). Ces travaux ont comme perspective applicative la
création d'un « Dictionnaire de voix » utile pour les tâches
d'indexation, de documentation, d'analyse et de fouille.

Il/elle sera amené(e) à collaborer avec l?ensemble des acteurs des
projets internes et externes du Département Recherche. Il aura la
responsabilité des développements informatiques liés à ces technologies
et participera à l?ensemble des tâches de spécification, conception et
rédaction de ces projets. Il sera également amené à participer à la
rédaction de réponses à des appels à projets de recherche et
développement, nationaux ou européens. Il/elle sera amené(e) à
participer à la rédaction de publications à caractère scientifique.

Il/elle contribuera avec les services opérationnels concernés et avec la
Direction des systèmes d'information à la mise en place à des fins
professionnelles d'un système de transcription automatique de la parole.
Il participera aux groupes de travail en charge de cette question.


  Activités principales

Dans ce cadre,  il/elle sera en charge de :

1/ Définir les axes de recherche et développement liés à l'analyse audio
et l'analyse de la parole :

  * 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.

2/ Assurer une R&D au service de l?Institut :

  * Proposer, préparer, coordonner et/ou participer à des projets de
    Recherche et Développement internes en lien avec les services
    opérationnels ;
  * Proposer, piloter et/ou participer à des actions de concertation et
    de réflexion internes dans le cadre de groupes de travail ;
  * Participer au déploiement de systèmes automatiques de la
    transcription de la parole en collaboration avec les services
    opérationnels de l?Ina et la Direction des systèmes d'information
    (DSI) : études des besoins, expertise technique, cahier des charges

3/ Réaliser des partenariats :

  * Proposer, préparer, coordonner, participer à des projets de
    Recherche et Développement collaboratifs, nationaux ou
    internationaux, à des instances de coopération scientifique et
    technologique (COMUE, Pôles de compétitivité, Groupes de recherche)
    en lien avec des partenaires académiques, institutionnels ou
    industriels ;

4/ Publier et diffuser des articles scientifiques :

  * Rédiger  des 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).

5/ Assurer une veille technologique dans son domaine.

6/ Participer aux tâches de gestion des ressources informatiques et
techniques du service.

7/ Réaliser un reporting de son activité.

8/ Encadrer des stagiaires et à terme des doctorants.


  Qualifications, diplômes, expérience

  *   Justifier d'un diplôme supérieur (Doctorat)  dans le domaine de
    l'analyse automatique de la parole ou de l'analyse audio, ou d?un
    parcours professionnel admis en équivalence.


  Compétences

  * Maitrise des techniques d'analyse automatique de la parole,
    d'analyse audio, de traitement de signal, d'apprentissage
    automatique, de développement informatique ;
  * Connaissance de la recherche académique et/ou industrielle ;
  * Maîtrise des techniques de conduite de gestion de projets ;
  * Maitrise des techniques de reporting ;
  * Connaissance du paysage audiovisuel français et du monde académique ;
  * Maîtrise des outils bureautiques ;
  * Très bonne maîtrise de l?anglais écrit et parlé.


  Aptitudes

  * Rigueur, méthode et organisation ;
  * Capacité d?analyse et de synthèse ;
  * Qualités relationnelles ;
  * Qualité d?expression écrite et orale ;
  * Créativité et imagination ;
  * Gestion du temps et des priorités ;
  * Force de proposition ;

  * Sens du service clients et du résultat.


  Liaison hiérarchique

Rattachement hiérarchique au Chef de service Groupes de recherches
audiovisuelles.


  Rémunération

42-47 k? / an selon expérience

logo_ina



*Jean Carrive *

*Responsable adjoint du Département Recherche*

Direction déléguée à l'Enseignement, à la Recherche et à la Formation

Ligne directe : +33 1 49 83 *34 29* - jcarrive@ina.fr
< mailto:jcarrive@ina.fr&gt;



*institut-national-audiovisuel.fr *
< http://www.institut-national-audiovisuel.fr/>

Top

TTS Research Engineer – Nuance Shanghai, China

Reporting to TTS manager, the research engineer will conduct innovative research and development with focus on TTS Front-end or Back-end technologies.

Responsibilities:

-As part of the TTS R&D organization, you will be contributing to the development of text-to-speech technology for all types of markets and platforms with focus on Asian languages.

Representative tasks will include:

- Improve TTS front-end or back-end with algorithm innovations.

- Develop product and tools,

- Maintenance and support (PS / Bug fixes)

- Active contribution to the improvement of all QA processes

Qualification:

Native Mandarin, Good English, additional Asia languages is a plus

- Experience with TTS research and development

- Experience with NLP research and development

- Excellent scripting / programming skills

- Experience with SCM tools

- Self-starter, team player

- Passion for quality

- Innovative and curious - 'free thinker'

- Master degree in EE/CS/Comp. Ling (or similar)

Please send your resume application to eva.li@nuance.com

Top

Stage Master 2 de Recherche en Traitement automatique des langues/Extraction d'information

Intitulé : Reconnaissance des Entités Nommées MÉDicales dans l'Oral (REMEDO)

Durée : 5 mois
Lieu : LIMSI-CNRS, Orsay, France
Rémunération : 554? par mois plus participation aux frais de transport en commun


*Contexte*
------------------------------
Devant l'augmentation toujours croissante de la masse de documents produits dans le
domaine médical, il devient de plus en plus difficile d'accéder aux informations
nécessaires au traitement et à la prise en charge des patients. Le recours à des méthodes
automatiques pour accéder aux informations contenues dans les textes devient alors
inévitable. Les méthodes d'extraction d'information sont aujourd'hui largement utilisées
afin d'identifier des données médicales comme des noms de patients, de médicaments ou de
maladies : 'La patiente <nom>Anne Onyme</nom> a été admise pour une <symptome>réaction
allergique</symptome> à la <traitement>pénicilline</traitement> le <date>21 janvier
2015</date>'.

Cette tâche se révèle toutefois particulièrement ardue lorsqu'il s'agit de traiter des
textes transcrits par des systèmes de reconnaissance de la parole. La qualité variable
des transcriptions automatiques et la variation terminologique compliquent la
reconnaissance des entités.


*Description du stage*
------------------------------
Nous posons l'exploitation de la dimension multimodale comme une piste d'amélioration des
systèmes d'extraction. Une hypothèse est que des paramètres acoustiques comme le rythme
ou l'intensité de la parole peuvent constituer des indices permettant d'aider le repérage
des entités nommées. Le but du stage sera d'éprouver cette hypothèse.

Le travail du stagiaire s'appuiera principalement sur les données issues de la tâche 1a
du challenge CLEF eHealth 2015, soit 200 enregistrements de dossiers de soins lus par une
infirmière ainsi que leur transcription annotée. NB : ces données sont en anglais, une
bonne connaissance de la langue est donc attendue.

Les tâches dévolues au stagiaire sont les suivantes :
 - rédiger un état de l'art sur la reconnaissance des entités nommées dans la parole
 - corriger les annotations préexistantes
 - développer une chaîne d'extraction d'entités nommées multimodale (qui s'appuiera
notamment sur le logiciel Wapiti)
 - utiliser des outils TAL et de traitement du signal pour extraire des traits multimodaux
 - évaluer et analyser l'influence des traits implémentés


*Profil recherché*
------------------------------
M2 Informatique ou linguistique avec parcours TAL

Compétences attendues :
 - Connaissances en programmation (langages de script)
 - Expérience avec des outils de TAL courants (étiqueteurs morphosyntaxiques, analyseurs
syntaxiques, ...) et avec des outils de traitement du signal (Praat)
 - Expérience des méthodes d'apprentissage automatique
 - Intérêt pour le traitement de l'audio et du texte
 - Compétences en anglais
 - Familiarité avec l'environnement Linux
 - Créativité et autonomie

NB : Aucune expérience du domaine médical n'est attendue.


*Encadrement*
------------------------------
Eva D'hondt
François Morlane-Hondère
Sophie Rosset
Pierre Zweigenbaum


*Pour candidater*
------------------------------
Merci d'adresser votre candidature avec un CV, une lettre de motivation ainsi que vos
notes de l'année universitaire en cours et de l'année dernière à Eva D'hondt
(eva.dhondt@limsi.fr) et François Morlane-Hondère (francois.morlane-hondere@limsi.fr)

Top

    ELDA (Evaluations and Language resources Distribution Agency), a company specialized in Human Language Technologies within an international context, is currently seeking to fill an immediate vacancy for Technical Engineer/Scientist (Project Manager) position.

Technical Engineer / Scientist

Under the supervision of the technical development manager, the responsibilities of the Technical Engineer/Scientist include specifying, designing and implementing tools and software components for language resources production frameworks and platforms, carrying out language resources quality control and assessment, as well as developing web services and applications.

This yields excellent opportunities for young, creative, and motivated candidates wishing to participate actively to the Language Technology field.

The task will mostly consist in participating in Web application development projects, language resources production projects, coordinating ELDA?s participation in R&D projects, while being also hands-on whenever required by the development team.

Profile:

-    PhD in Computer Science
-    at least 2 years of  experience in Natural Language Processing (or Information retrieval) and / or Web application development
-    Good knowledge of Linux and open source software
-    Proficiency in Python or other high-level dynamically-typed programming language, such as Ruby
-    Hands-on experience in Django; proficiency in Django-CMS is a plus
-    Good knowledge of Javascript and CSS
-    Knowledge of SQL and of an RDBMS (PostgreSQL preferred)
-    Good knowledge of Natural Language Processing
-    Dynamic and communicative, flexible to combine and work on different tasks
-    Ability to work independently and as part of a multidisciplinary team
-    Proficiency in French and English
-    Citizenship (or residency papers) of a European Union country

Applications will be considered until the position is filled. The position is based in Paris.

Salary: Commensurate with qualifications and experience.

Applicants should email a cover letter addressing the points listed above together with a curriculum vitae to:

Khalid Choukri
ELDA
9, rue des Cordelières
75013 Paris
FRANCE
Mail : job@elda.org

For further information about ELDA, visit:
http://www.elda.org

Top

The TTS team at Google is looking for a Language Engineer to help improve synthesis in English and French.

Based in Google London offices, you will be helping with technical tasks involved in creating a speech synthesizer.  This includes:

1. Developing rules for a text normalization system;

2. Large scale data mining;

3. Customizing language building tools for English and French.

4. Text-to-Speech quality evaluation and testing

Requirements:

1. Recent Computer Science graduate or closely related discipline

2. Native-level speaker in French/English and fluent in English.

3. Proficiency in Unix/Version Control System and a modern programming language (Python/C++ preferred)

4. Ability to build and understand regular expressions

5. Interest in data mining and natural language processing a plus

This is an opportunity to work on cutting edge technology in a dynamic team of world-class experts.

Project duration: 6-11 months (with potential for extension)

**This is not a permanent position but a contract position through an employment agency. Applicants must be currently authorized to work in the UK.**

For immediate consideration, please email your CV and cover letter in English (PDF format preferred) with 'Language Engineer English or French' in the subject line. 

Application Deadline: (Open until filled)

Email Address for Applications: tts_jobs@google.com

Top

Machine learning and language technology

Reykjavik University is looking for ambitious candidates to work on development and
implementation of speech recognition and other language technologies. The development of
speech recognizers applies machine learning on big data sets of text and speech
recordings. The machine learning that is used in the projects is mostly implemented and
available in open source software. The work typically includes gathering and preparing
data, setting up and configuring the machine learning procedures, run experiments and
design the interface for users and other software. The positions are for one year with
possibility of extensions.

Specialist in machine learning
The main focus of this job is to apply machine learning on big text and speech datasets
to develop and train automatic speech recognizers. The software that is used in the
project is called Kaldi, which demands a high skill in the use of Linux and associated
tools. The work is to set up and evaluate computational models (finite state transducers,
hidden Markov Models and deep neural networks) on large datasets.

Skills:
? BSc/MSc degree in mathematics, statistics, engineering, computer science or similar.
? Knowledge of computational modeling is preferable (e.g. differential equations, neural
networks, linear models).
? Good knowledge of Linux is necessary.
? Good skills in writing and understanding shell scripts are preferable (bash, awk, sed).
? Good programming skills are necessary (e.g. C++, Java or Python).

Researcher in machine learning
The main focus of this job is to carry out research on speech recognition using deep
neural networks. The theoretical part of the work can either concentrate on parameter and
model optimization with respect to speech recognition performance or on learning setup
and model configuration with the aim to automate training of speech recognizers. The
group is already using open source speech recognition solutions of Kaldi, Tensorflow and
Theano. Some systems are already in operation while others are in the process of being
implemented. Design improvements and adaptation will continue in the coming months and
years, so the research will have a very direct practical impact.

Skills:
? MSc/PhD degree in applied mathematic, statistics, computational engineering or computer
science is preferable.
? Knowledge of mathematical modeling is preferable (e.g. differential equations, neural
networks, linear systems).
? Good skills in applying and analyzing algorithms.
? Good knowledge of Linux is preferable.
? Ability to use shell scripts is preferable (bash, awk, sed).
? Good programming skills are necessary (e.g. C++, Java or Python).

For further information contact Jón Guðnason, (jg@ru.is) Assistant Professor in School of
Science and Engineering.
Applications should be submitted before the end of 15th of April 2016 but strong
applications might be considered earlier.
Please submit your application through links provided at:
http://radningar.hr.is/storf/viewjobonweb.aspx?jobid=2729

Top

PhD position in AVSR at Trinity College Dublin, Ireland

With a link to this advert:

http://adaptcentre.ie/careers/tcd_phd_IG_PhD5_D.pdf

Top

 1 post-doc in Brain- and biosignal-based speech recognition

https://beta.iit.it/careers/openings/opening/66-postdoctoral-position-in-brain-and-biosignal-based-speech-recognition

- 1 post-doc in New techniques for vision-assisted speech processing with event-drive cameras (within the EU H2020 Ecomode project) 

https://beta.iit.it/careers/openings/opening/71-postdoctoral-position-in-new-techniques-for-vision-assisted-speech-processing

Top

Un poste de Maître de Conférences en informatique (section 27) est mis au concours pour
la campagne 2016 au Centre d'Enseignement et de Recherche en Informatique de l'Université
d'Avignon (ceri.univ-avignon.fr).

La personne recrutée effectuera sa recherche au sein du LIA (lia.univ-avignon.fr).

Le profil du poste est consultable sur lia.univ-avignon.fr rubrique Emplois et sur
GALAXIE :

- Informatique - Profil indexation audio/biométrie vocale  (Poste 088 / Galaxie 4080) -
https://www.galaxie.enseignementsup-recherche.gouv.fr/ensup/ListesPostesPublies/ANTEE/2016_1/0840685N/FOPC_0840685N_4080.pdf

Contacts :

Enseignement : Corinne Fredouille corinne.fredouille@univ-avignon.fr - Directrice des
Etudes du CERI et Fabrice Lefèvre fabrice.lefevre@univ-avignon.fr - Directeur du CERI

Recherche : Fabrice Lefèvre fabrice.lefevre@univ-avignon.fr - Directeur du CERI,
Directeur LIA par interim

Top

Trois postes d'enseignants-chercheurs en informatique sont à pourvoir à l'Université du Maine lors de la campagne de recrutement 2016 : un poste de Professeur et deux postes de Maîtres de conférences.

Les personnes recrutées sur chacun de ses postes effectueront leurs travaux de recherche au LIUM (Laboratoire d'Informatique de l'Université du Maine) :

- Le poste de Professeur est rattaché au Département d'informatique de  l'UFR Sciences de l'Université du Maine. Le profil recherche est spécialisé dans le domaine du traitement automatique du locuteur. Le profil enseignement  vise les matières fondamentales de l'informatique, incluant la capacité à enseigner la théorie des langages.
Plus d'info :
https://www.galaxie.enseignementsup-recherche.gouv.fr/ensup/ListesPostesPublies/ANTEE/2016_1/0720916E/FOPC_0720916E_4154.pdf

- Un poste de Maître de conférences est rattaché au Département d'informatique de l'UFR Sciences de l'Université du Maine. Le profil recherche est spécialisé dans le domaine de la reconnaissance automatique de la parole. Le profil enseignement  vise les matières fondamentales de l'informatique, incluant la capacité à enseigner la théorie des langages.
Plus d'info :
https://www.galaxie.enseignementsup-recherche.gouv.fr/ensup/ListesPostesPublies/ANTEE/2016_1/0720916E/FOPC_0720916E_4153.pdf

- L'autre poste de Maître de conférences est rattaché au Département Gestion des Entreprises et des Administrations de l'IUT du Mans. Le profil recherche est spécialisé dans le domaine de l'apprentissage automatique et de la fouille de données textuelles. Le profil enseignement concerne l'informatique de gestion, les bases de données et l'informatique appliquée à la gestion des entreprises.
Plus d'info :
https://www.galaxie.enseignementsup-recherche.gouv.fr/ensup/ListesPostesPublies/ANTEE/2016_1/0720083Z/FOPC_0720083Z_4170.pdf

Top

Vous trouverez à l'URL suivante et en pièce jointe une offre de thèse ministérielle à l'IRISA intitulée 'Transformation de registres par extraction de motifs langagiers' : https://www-expression.irisa.fr/files/2011/07/sujet1.pdf . Merci de diffuser auprès de personnes éventuellement intéressées.

Pour plus de précisions ou pour postuler, merci de contacter :

- Pascale Sébillot : pascale.sebillot@irisa.fr

- Nicolas Béchet : nicolas.bechet@irisa.fr

- Gwénolé Lecorvé : gwenole.lecorve@irisa.fr

Date limite de candidature : 30 avril 2016.

Top

We are happy to advertise for a Post Doctoral Position in Machine Learning at Univ. Lille, France

Topic
Machine Learning for Human-Robot Interaction

Job description
This position is offered in the framework of the BabyRobot H2020 (www.babyrobot.eu) project involving 8 partners across Europe (including France, Sweden, UK, Greece, Germany and Denmark). The project focuses on interactive robotics and especially on interaction with children. 

Breakthroughs in core robotic technologies are needed to support this research mainly in the areas of motion planning and control in constrained spaces, gestural kinematics, sensorimotor learning and adaptation. In addition, new models of interaction need to be developed. Because of the human being in the loop, standard control theory can hardly be applied. For this reason, machine learning methods such as reinforcement and imitation learning have been identified as candidates to address these issues in a unied framework. Therefore, the applicant will be involved in research in core machine learning applied to control and interaction. Several directions of research are envisioned. First, recent works on stochastic games [3] applied to dialogue management [1] can be further investigated so as to be adapted to multimodal and multiparty interaction scenarios. Second, the 'learning from demonstration' (LfD) [4] paradigm can be adapted to the adversarial case so as to transfer interactional behaviours from actual human-human interactions to machines. Other  topics can be investigated such as inverse reinforcement learning [2] or transfer learning.

Profile
The applicant should have completed a PhD in computer science, statistical learning or robotics. The ideal candidate will have a strong background in machine learning and especially in reinforcement learning or stochastic games. Experience in interactive systems (spoken dialogue systems, interactive robotics, human-machine interfaces) would be much appreciated. The recruited person will be involved in the management of the project, participate to consortium meetings and contribute to deliverables. Therefore, good communication skills and autonomy are mandatory. Preference will go to candidate with a strong publication record.

Work environment
The position is offered in the Sequential Learning (SequeL) research team (joint team between Inria, Univ. Lille and CNRS) located in Lille, France. SequeL is a world-leading group in reinforcement learning, bandit theory and recommendation systems involving 30 members (including 10 permanent staff members). The team's working language is English. The team is part of the French National Institute for Computer Science and Mathematics (Inria) as well as the Computer Science and Signal Processing laboratory of Lille (CRIStAL). Lille is the capital of the north of France, a metropolis with 1 million inhabitants, with excellent train connection to Brussels (30 min), Paris (1h) and London (1h30).

How to apply
The application should include a brief description of research interests and past experience, a CV, degrees and grades, motivation letter, relevant publications, letter(s) of recommendation and contact information to reference persons.

Details
Application deadline: 30th of April 2016
Starting date: May or June 2016
Duration: 24 months (can be extended)
Salary (after taxes): 2100 euros

Contacts
Olivier Pietquin: olivier.pietquin@univ-lille1.fr
Bilal Piot: bilal.piot@univ-lille1.fr

References
[1] Merwan Barlier, Julien Perolat, Romain Laroche, and Olivier Pietquin. Human-machine dialogue as a stochastic game. In Proceedings of the 16th Annual SIGdial Meeting on Discourse and Dialogue (SIGDIAL 2015), pages 2{11, Prague (Czech Republic), September 2015.
[2] Edouard Klein, Matthieu Geist, Bilal PIOT, and Olivier Pietquin. Inverse Reinforcement Learning through Structured Classication. In Advances in Neural Information Processing Systems (NIPS 2012), pages 1007{1015, Lake Tahoe (NV, USA), December 2012.
[3] Julien Perolat, Bruno Scherrer, Bilal Piot, and Olivier Pietquin. Approximate dynamic programming for two-player zero-sum markov games. In Proceedings of the International Conference on Machine Learning (ICML 2015), Lille (France), July 2015.
[4] Bilal Piot, Matthieu Geist, and Olivier Pietquin. Learning from demonstrations: Is it worth estimating a reward function? In Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, and Filip Zelezny, editors, Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2013), volume 8188 of Lecture Notes in Computer Science, pages 17{32, Prague (Czech Republic), September 2013. Springer.

Top

Research Associate Position at York University, Toronto, Canada

The Lassonde School of Engineering, York University (http://lassonde.yorku.ca/) is sponsoring a fulltime
research associate position in deep learning for natural language processing (NLP). This position
is comparable with a research professorship (with annual salary up to $85k), an initial two-year
appointment but extendable. This research position is created to support the cutting-edge research
activities in NLP, particularly applying deep learning to the challenging NLP or AI problems, including
(not limited to) information extraction, language understanding and inference, and probabilistic
reasoning.
If you are interested, please email your CV to:
Prof. Hui Jiang (hj@cse.yorku.ca) (http://wiki.eecs.yorku.ca/user/hj/)
iFLYTEK Laboratory for Neural Computing and Machine Learning (iNCML)
(http://wiki.eecs.yorku.ca/lab/MLL/start)
Department of Electrical Engineering and Computer Science
The Lassonde School of Engineering, York University
The deadline is May 15, 2016.

Top

A new PhD position is open in 'Multilingual Affective Speech Synthesis' at Idiap Research
Institute:
 http://www.idiap.ch/education-and-jobs/job-10193

Candidates with knowledge of French and English would be at an advantage.

Top

Speech Recognition Researcher position (full-time) at Sony, in Stuttgart, Germany. For details, please check out  http://www.stuttgart.sony.de/home/career-jobs/open-positions.html. We welcome your e-mail to denise.biermann@eu.sony.com.

Top

EMR.AI Inc., San Francisco, CA

RESEARCH SCIENTIST, NATURAL LANGUAGE PROCESSING

Headquartered in San Francisco, CA, EMR.AI Inc. is a leading provider of AI solutions to the medical sector. EMR.AI transforms unstructured information, in form of written, spoken, or typed reports, clinical test results, and radiographs into international standard codes saved in common EMR systems. The wealth of discrete medical data provided through this transformation in conjunction with EMR.AI's suite of medical analytics solutions enables stakeholders, practitioners, researchers, health providers, and policy makers to obtain a comprehensive picture of the available medical data in their organization.

SUMMARY

EMR.AI Research & Development has openings for Research Scientists in the field of Natural Language Processing in our Downtown San Francisco offices. Scientists will work on projects spanning a variety of tasks including the semantic interpretation of written and spoken medical reports, the design of language models for a variety of NLP tasks and speech recognition, the summarization of written and spoken language in the medical domain, the incorporation of lexica, ontologies, relational databases, and other sources of structured and unstructured knowledge sources into EMR.AI’s medical NLP tool set, and others. This is a unique opportunity to be part of a cutting-edge R&D team in the epicenter of the world’s AI tech industry with true impact on medical research.

RESPONSIBILITIES

 Process huge corpora of medical textual documents to perform syntactic and semantic analyses and train, tune, and test probabilistic and other data-driven models, using both existing tool benches, proprietary and open-source, as well as self-developed algorithms and techniques.

 Produce high-quality programs and scripts to embed scientific algorithms into effective prototypes and demos to be shared with EMR.AI’s leadership team, its customers, partners, and vendors.

 Create and document technological innovations by means of patent disclosures, scientific publications, media alerts, and other channels.

 Work closely with EMR.AI’s speech processing team and its software engineering division to produce innovative and effective solutions for a range of AI products and services in the medical domain.

 Represent the R&D division in communications with EMR.AI’s leadership team, its customers, partners, and vendors at meetings, conventions, and other venues as well as in written statements.

SKILLS

PhD in computer science, computational linguistics, electrical engineering, or a related field. Experience in the state of the art of NLP and its standard tools is required. Candidates must be very skilled in programming and must have a proven scientific track record. They must be excellent team players, including with distributed teams, and strong in oral and written English communication. Knowledge of the US medical sector is desirable, so are experience with start-ups and strong scientific connections throughout the Bay Area and beyond.

BENEFITS

EMR.AI offers competitive salaries, an excellent benefit package, and a stimulating work environment in the heart of San Francisco with manifold local, domestic, and international commercial and academic partnerships.

HOW TO APPLY

Please send your application documents to jobs@emr.ai

CONTACT

EMR.AI Inc. 90 New Montgomery St San Francisco, CA 94105,

USA phone: +1-415-200-8535

e-mail: info@emr.ai www: http://emr.ai

Top

A 3-year postdoctoral research position in speech processing is available in the Sigmedia Group in Trinity College Dublin, Ireland.

Full details of the position are given in the advert available at: http://adaptcentre.ie/careers/TCD_postdoc_themeD-2.pdf

Top

Postdoctoral Position in Linguistics (Prosodic Phrasing and Discourse Comprehension), Université catholique de Louvain

The Institute for Language & Communication of the Université catholique de Louvain (Belgium) is currently seeking a postdoctoral researcher to perform corpus analysis and experimental research on the role of prosody in discourse comprehension. The successful candidate will work under the supervision of Prof. Anne Catherine Simon and will join the project “PhraDiCo: Prosodic phrasing for discourse comprehension. Perception of prosodic boundaries and their contribution to the construal of discourse coherence”. He/she will be employed on a fixed-term contract for 24 months.

Project Description

[PhraDiCo] Prosodic phrasing for discourse comprehension. Perception of prosodic boundaries and their contribution to the construal of discourse coherence. Prosodic phrasing is central to language comprehension and discourse coherence. Spoken language is highly transitory and dynamic. Speech is processed in real-time, as the hearer allocates his attention to each incoming unit and integrates it into a coherent whole. Speech is chunked into prosodic units which are presumably used as basic units of discourse processing. During its first phase, this project aims to explore how ordinary listeners (as opposed to trained experts) perceive prosodic boundaries in spoken language. What is the relationship between the prosodic cues (pauses, lengthening, melodic discontinuity etc.) and the perceived strength of prosodic boundaries? To what extent does the syntactic structure contribute to the perception of prosodic boundaries? Are naïve listeners consistent in their appreciation of boundary strength on word boundaries? Once those questions have been sufficiently tackled, we will focus on analysing the contribution of prosodic boundaries to discourse coherence: relational coherence, which seeks to establish discourse relations between discourse “building blocks”, and referential coherence, i.e. the identification of large-scale discourse topics. Four perceptual experiments have been designed to investigate (i) the acoustic and linguistic factors involved in the perception of prosodic boundary strength; (ii) the influence of speaking styles variability (speech rate, pitch register) on prosodic boundary perception; (iii) the contribution of prosodic units to the construal of discourse relations and (iv) to the identification of large-scale discourse topics.

The project is undertaken by the research centre “Valibel – Discours & Variation” (Discourse & Variation, www.uclouvain.be/valibel) and is funded by F.S.R. – FNRS (www.frs-fnrs.be).

Job Description

• Discursive and prosodic analysis of speech data (transcription, alignment and annotation).

• Design of experimental procedures and preparation of speech samples for perceptual experiments.

• Organisation of on-line and off-line speech perception experiments (recruitment of participants, technical and practical aspects of execution etc.).

• (Statistical) Analysis of the experimental results using databases and specialised tools.

The appointed researcher will work in close collaboration with the project’s supervisor and another postdoctoral researcher. He/she will participate in research leading to scientific publications.

Qualifications

• PhD in Linguistics (discourse analysis, experimental linguistics, cognitive approach to discourse comprehension, syntax-prosody interface) obtained not more than 6 years before the starting date.

• Experience in discourse annotation (topic-focus, discourse relations), in experimental research (perceptual studies), and/or in prosodic analysis.

• Expertise in statistical methods for analysing linguistic data is desirable.

• Knowledge of the Praat software is an asset.

• Native-like command of French and good command of academic English.

Place of employment: Louvain-la-Neuve, Belgium (30 km south of Brussels). With 21000 students and 5000-member staff, the University of Louvain is the largest university of the Brussels and Wallonia regions of Belgium.

Contract length: 24 months.

Contract term: Full-time

Starting date: July 2016

Deadline for applications: 5 June 2016

Applications (motivation letter, detailed CV, 1-3 recommendation letters and 3 relevant publications), should be sent in electronic format to Prof. Anne Catherine Simon (anne-catherine.simon@uclouvain.be).

Top

PhD positions are available in our group at Inria, in France, on deep learning for:
- speech enhancement
- robust speaker recognition
- robust speech recognition
- language model adaptation

Details:
http://www.adum.fr/as/ed/voirproposition.pl?langue=en&site=IAEM&matricule_prop=12468
http://www.adum.fr/as/ed/voirproposition.pl?langue=en&site=IAEM&matricule_prop=12465
http://www.adum.fr/as/ed/voirproposition.pl?langue=en&site=IAEM&matricule_prop=12473
http://www.adum.fr/as/ed/voirproposition.pl?langue=en&site=IAEM&matricule_prop=10773

Profile:
Candidates must hold an MSc in computer science, machine learning, signal processing, or
applied mathematics, or be about to obtain one. Programming experience in Python or C/C++
is a must.

Working Environment:
Nancy is one of the top cities to study in France with 50,000 students, cheap
accomodation, a vibrant cultural scene, and good connections to Paris (1.5h), Luxemburg
(1.5h), Belgium, and Germany. Inria Nancy is a 500-people research institute dedicated to
computer science. The Multispeech team (https://team.inria.fr/multispeech/) is a
30-people group covering various fields of speech science, with a strong emphasis on
statistical machine learning and signal processing.

To apply:
Click on 'candidater' at the bottom of the webpage. You will be asked for a detailed CV,
BSc and Msc transcripts and diplomas, publications, and recommendation letters. Please
apply as soon as possible. There will be a first cutoff date on May 31 and a second one
on June 30.

--
Emmanuel Vincent

Top

PhD Position: Merging acquisition and processing of cineMRI of the vocal tract

Subject

Tracking the position of speech articulators along time is crucial to understand speech production better. For a long time X-ray imaging was the only technology able to acquire images at a sufficiently high sampling frequency (around 50 images per second) for visualizing articulatory gestures. However, this technique has been abandoned at the end of the eighties because of the health hazard implied by ionizing radiations. Furthermore, since the whole vocal tract is projected on the image plane contours of organs (especially the mandible, teeth and tongue) overlap on the images making the processing of images very difficult.

The interest of Magnetic Resonance Imaging (MRI) is to provide an excellent contrast of soft tissues for a slice placed in any orientation and dynamic MRI is acknowledged as a powerful tool for imaging speech production [3].  However, current performance of cineMRI remains inadequate in terms of sampling rate and spatial resolution, and the objective of this thesis is to develop more efficient acquisition protocols and algorithms.

The objective is to develop protocols by exploiting the latest advances in MRI, particularly parallel imaging and reconstruction under parsimony constraints called ?compressed sensing? [1]. IADI laboratory developed MRI reconstruction techniques with movement compensation [2] and multi-slice dynamic reconstruction enabling super resolution. These techniques have been already applied to cardio-respiratory movements by using physiological signals (ECG and respiratory) as constraints for the reconstruction algorithms.

A first preliminary work consisting of applying these techniques to the domain of speech production  has been carried out [4]. A second work was dedicated to the development of an acquisition protocol based on ?compressed sensing?. The idea is to exploit the parsimony of the image Fourier transform coefficients in order to acquire only a small number of them, and then to reconstruct the image in an optimal manner.

However, it is possible to do better since the speech signal is acquired simultaneously then denoised before being segmented into speech sounds. Therefore, the contribution of each line acquired in the image Fourier space can be related to the speech sound it corresponds to, and one can take advantage of this information to improve the resolution of reconstructed images. This  idea will be exploited with the objective of realizing a proof of concept of automatic acquisition/reconstruction of MRI images of vocal tract during speech production. We would like to go further by utilizing the knowledge of the speech sound and the approximative vocal tract shape predicted for the sound by an articulatory model to pilot acquisition.

Keywords: MRI acquisition, compressed sensing, speech processing, articulatory modeling, vocal tract

Some references

[1]Michael Lustig, David Donoho, and John M. Pauly. Sparse MRI: The application of compressed sensing for rapid MR imaging. MAGNETIC RESONANCE IN MEDICINE, 58(6):1182?1195, December 2007.

[2]F. Odille, P. A. Vuissoz, P. Y. Marie, and J. Felblinger. Generalized reconstruction by inversion of coupled systems (GRICS) applied to free-breathing MRI. Magn Reson Med, 60(1):146?57, July 2008.

[3]Andrew D Scott, Marzena Wylezinska, Malcolm J Birch, and Marc E Miquel. Speech MRI: Morphology and function. Physica Medica, 30(6):604?618, 2014.

[4]P.A. Vuissoz, F. Odille, Y. Laprie, E. Vincent, G. Hossu, and J. Felblinger. Speech Cine SSFP with optical microphone synchronization and motion compensated reconstruction. In ISMRM Workshop on Motion Correction in MRI, Tromso, Norvège, May 2014.

Environment

Both laboratories IADI and LORIA have developed a narrow and fruitful collaboration for years which in particular resulted in the development of a ?compress sensing? acquisition algorithm and in a research contract on articulatory synthesis. A working environment covering articulatory modeling and MRI data acquisition domains is now available and will offer very favorable conditions for this work.

Supervisors

·       Pierre-André Vuissoz (IADI ? Imagerie Adaptative Diagnostique et Interventionnelle, unité INSERM U947) pa.vuissoz@chu-nancy.fr

·       Yves Laprie (MultiSpeech team at LORIA ? Laboratoire Lorrain de Recherche en Informatique et ses Applications, UMR 7503)

Application

We are looking for a highly motivated person with a master degree in computer sciences, applied mathematics or computer sciences. The applicant should have a solid background in signal processing (and Matlab software) and computer sciences. Knowledge in speech processing will be also appreciated.

Interested applicants should send their application file to Yves.Laprie@loria.fr and pa.vuissoz@chru-nancy.fr:

a)     Motivation letter,

b)     CV,

c)     academic transcripts (with explanation of the grade scale adopted),

d)     2 references (letters or names)

Expected start date: 1st October 2016

Top

Title: Senior Speech Analytics Engineer

Job Description

SRI’s Speech Technology and Research (STAR) Lab seeks a self-motivated, team-oriented, experienced leader and innovator to work in the area of speaker state analysis (for example, emotion and health states). The work will include advancing technology capabilities, determining client needs and understanding client data, winning new funding, interacting with clients, both government and commercial, and leading current or new projects in this area. The successful candidate must be proactive and entrepreneurial. This is an opportunity to have a significant impact in an emerging research area.

STAR Lab engages in leading-edge research in speech recognition, speaker characterization, speaker and language identification, machine translation, natural language processing and other areas of speech/language technology, offering opportunities from basic research to prototyping, productization, and widespread deployment. The multidisciplinary research team consists of excellent speech researchers, linguists and software engineers. Characteristics of STAR staff are enthusiasm, self-motivation, initiative, passion for learning, taking ownership, thriving in a flat organizational hierarchy, and a desire to control their own career paths.

SRI International is a premier nonprofit research organization based in Menlo Park, California with a mission to create world-changing solutions making people safer, healthier, and more productive.

Located in the heart of Silicon Valley, the world’s center for innovation and technology, SRI’s focus spans everything from basic research to delivered systems, government and commercial work and spinning off successful companies like SIRI. Flexible cross-laboratory teams often form dynamically to solve challenging problems spanning multiple disciplines.

Requirements

A PhD degree or equivalent with at least 10 years of experience in speech or NLP technology. Prior interest in the area of speaker characterization is an advantage. Experience of leading teams of projects in either academia or industry along with a record of either successful proposals (government or industry) or managing a start-up in the speech area is required. Strong oral and written communication skills in English are expected. US citizenship is a plus but not required. Must be flexible to traveling.

Apply online at www.sri.com/careers

Job ID: 1020BR

SRI is an Equal Employment Opportunity/Affirmative Action Employer

Top

Research Associate Position at York University, Toronto, Canada

The Lassonde School of Engineering, York University (http://lassonde.yorku.ca/) is
sponsoring a fulltime
research associate position in deep learning for natural language processing (NLP). This
position
is comparable with a research professorship (with annual salary up to $85k), an initial
two-year
appointment but extendable. This research position is created to support the cutting-edge
research
activities in NLP, particularly applying deep learning to the challenging NLP or AI
problems, including
(not limited to) information extraction, language understanding and inference, and
probabilistic
reasoning.
If you are interested, please email your CV to:
Prof. Hui Jiang (hj@cse.yorku.ca) (http://wiki.eecs.yorku.ca/user/hj/)
iFLYTEK Laboratory for Neural Computing and Machine Learning (iNCML)
(http://wiki.eecs.yorku.ca/lab/MLL/start)
Department of Electrical Engineering and Computer Science
The Lassonde School of Engineering, York University
 

Top

Speech Technologist @ Voice Tech Startup!

Location: Belmont, MA

Available: Immediately

VocaliD is a voice technology start-­up that is bringing speaking machines to life by creating

personalized digital voices. Our award-­winning technology is grounded in over a decade of

research at Northeastern University and has enabled us to attract Small Business Innovation

awards from the National Science Foundation and the National Institutes of Health. We

successfully delivered a set of beta voices in 2015 and have a waiting list of pre-­orders

though our oversubscribed crowdfunding campaign. We are now seeking an experienced

research-­based speech technologist to join our team as we launch our personalized voice

service in mid 2016.

Communications applications and devices are getting smarter and using more sophisticated

AI, yet the voices remain robotic and unnatural. Until now, the cost and time to build a custom

voice has been prohibitive. VocaliD creates personalized digital voices at scale for use on

any device that speaks. Our proprietary voice search and speech blending algorithms

leverage our “Human Voicebank”, a collection of 3.5 million of recordings crowdsourced from

around the world. Our breakthrough is that we only need 2-­3 seconds of someone’s voice to

(re)create a voice when combined with recordings of a matched speaker from the Voicebank.

Our initial market addresses the 10M+ people worldwide who use a machine to speak.

VocaliD enables these individuals to speak in their own voice instead of the familiar “Stephen

Hawking” voice. Join our dynamic team as we push the envelop on innovation while having

real social impact!

Responsibilities:

-­ Create tools for filtering and parsing recorded voices

-­ Implement machine learning algorithms to match donor and recipient voices

-­ Enhance source-­filter separation and voice conversion algorithms

-­ Design and implement novel algorithms for tracking and monitoring speech changes

-­ Create a framework for algorithmic synthesis of voices from donor samples

-­ Implement a SaaS framework for voice deployment

Required Qualifications:

-­ MS or PhD in Electrical or Computer Engineering, Computer Science or related field

-­ Experience programming in C/C++, Python, Java

-­ Experience productizing algorithms from prototypes in Matlab (or other)

-­ Experience with Digital Signal Processing and ideally speech/voice technologies

-­ Experience with AWS services EC2, S3, RDS (Postgres), Route 53

-­ Experience with Windows and Linux

If you are interested in joining a thriving and passionate team, please submit a cover letter

and resume to rupal@vocaliD.co

Visit us at www.vocaliD.co for more information about VocaliD.

Top

Call for Postdoctoral Positions in Cognitive Science/Psychology/Linguistics

Institution: Laboratoire Parole et Langage (CNRS, Aix-Marseille Université)

Location: Aix-en-Provence, France

No. of positions: 1

Duration: 2 years (see below)

Application deadline: July 20, 2016

The Laboratoire Parole et Langage (CNRS, Aix-Marseille Université, Aix-en-Provence, FR) invites applications for one postdoctoral fellowship supported by a grant from the French National Research Agency (ANR). The funded project aims at exploring the role of prosody in speech planning and how planning strategies are affected both by the pragmatic situation and by individual cognitive-emotional abilities. Cognitive-emotional constraints are investigated by comparing healthy adults and clinically impaired individuals (patients affected by multiple sclerosis). The project involves an interdisciplinary team from across the Laboratoire Parole et Langage (which includes experts in linguistics, speech analysis, psychology) including collaboration with the 'Pôle de Neurosciences Cliniques' of the Hospital la Timone (Marseille) and the Neurology Department of the Centre Hospitalier du Pays d'Aix (Aix-en-Provence).

Applicants must have a Ph.D. in a relevant field of study (e.g., Cognitive Science, Linguistics, Psychology), and a strong background in experimental design and statistics. Special attention will be given to candidates with expertise in cognitive aspects of social coordination and in emotion in spoken language. Experience with psychophysiological methodologies and conducting studies with neurological patients is also highly desirable.

The postdoctoral appointment is for a duration of up to two years depending on the starting date, and subject to review after the first year. Applicants should hold a PhD or expect to complete a PhD by the starting date. The starting date is flexible, though the position should be filled by the beginning of the fall of 2016.

Applications should include (i) a cover letter that relates the applicants’ experience and interests to the project, (ii) a comprehensive CV, (iii) the names and contact information of two references, and (iv) a PDF copy of all publications or a list of links where these can be accessed.

Applications in French or English may be sent by email to Elisa Sneed German at elisa.sneed@lpl-aix.fr.

For further inquiries regarding the position or the project, please contact Caterina Petrone (Principal Investigator) at caterina.petrone@lpl-aix.fr.

Top

=============================================
PhD Positions in Signal Processing for Speech Communication
=============================================

The Signal Processing and Speech Communication Lab (SPSC) of Graz University of
Technology is seeking to fill one PhD position in the area of signal processing for
speech communication.
The Ph.D. research will be embedded in the FWF project P 28070-N33 entiteld 'Phase-Aware
Signal Processing for Speech Communication' led by Dr. Pejman Mowlaee.

Required skills:
* M.Sc. degree in relevant field (Audio engineering, EE, CS, Telematics)
* Strong background in statistical signal processing and speech processing
* Independent and self-motivated working
* Excellent communication skills, fluency in English

The SPSC is a research and education center in focused on different aspects of signal
processing covering applications in speech/audio communication, telecommunications and
wireless communication. For more details on the ongoing research and publications carried
out in the project you are referred to PhaseLab webpage:
https://www2.spsc.tugraz.at/people/pmowlaee/PhaseLab.html.

Please send your application (CV, motivation letter, list of grades, and names of
references) to pejman.mowlaee@tugraz.at. Application deadline is August 1st, 2016.

Top

Nous offrons un contrat doctoral de 3 ans portant sur la « Caractérisation et la génération de l'expressivité en fonction des styles de parole pour la construction de livres audio ». Des informations sur ce travail sont disponibles à : https://www-expression.irisa.fr/files/2016/06/phd_caracterisation_generation_livre_audio.pdf. Cette thèse sera effectuée en co-direction entre l?IRISA et le LLF (plus précisément LABEX EFL). 

Top