Appel à chercheurs 2017-2018

Nouveaux dispositifs de soutien à la recherche à l’Ina :

Chercheurs associés et bourses de recherche

Afin d’encourager le développement de travaux scientifiques menés à partir de ses fonds et des outils d’analyse qu’il développe, l'Ina a décidé de créer en 2017 deux nouveaux dispositifs de soutien à la recherche et à la valorisation scientifique de ses collections :

• l’octroi d’un statut de chercheur associé à l’Ina
• l’attribution de bourses de recherche

Par ces dispositifs, l’Ina entend accompagner des doctorants et des chercheurs dans la réalisation de projets de recherche originaux et innovants portant sur (ou faisant appel à) ses collections, ou portant sur l’analyse ou le traitement des images et/ou des sons et/ou de données associées.

L’Institut offre aux chercheurs sélectionnés un accueil privilégié, assorti de divers soutiens matériels.

Ces nouveaux dispositifs sont complémentaires des prix de l’Inathèque créés en 1997, et ajoutent un nouveau volet à la politique scientifique de l’Institut.

Le règlement de l’appel est disponible sur le site de l’Inathèque : http://www.inatheque.fr/actualites/2017/mai-2017/appel-chercheurs-2017-2018.html

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Le service audio de la Police Technique et Scientifique (Ecully, près de Lyon, France) recherche des vacataires pour effectuer un travail de segmentation et de correction d'alignement automatique dans le cadre d'études phonétiques.
Le profil suivant est recherché:

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Department of Computer Science, University of Crete, Greece
Post-doctoral Research Associate in Advanced Deep Neural network Architectures for ASR  (Fixed Term)
 
SALARY: €24000-€28000 per year
CLOSING DATE: 30 June 2017
REFERENCE: ASR1
TO APPLY: Send detailed CV, a motivation letter and 3 major publications to yannis@csd.uoc.gr
 
In the past few years, Deep Neural Networks (DNNs) have achieved tremendous success for many supervised machine learning tasks, including acoustic modelling for Automatic Speech Recognition (ASR). Advanced models such as Convolutional Neural Networks (CNNs) and Long Short Term Recurrent Neural Networks (LSTMs) have contributed to recent empirical breakthroughs. Network depth has played perhaps the most important role in these successes. However, increased depth represents challenges in the optimization of the network and despite the efforts to overcome these challenges some of the optimization issues are still important resistant. Advanced networks such as highway networks and (wide) residual networks seems to offer solutions to these issues.
This position represents an ideal opportunity to work in or move into advanced deep neural networks, as it will involve collaborating widely across academia and industry, and working on one of the most pressing research areas of machine learning for the development of robust ASR systems.
Based in Heraklion Crete the post will be with Prof. Yannis Stylianou and Dr. Vassilis Tsiaras as part of the speech processing group within the Department of Computer Science at the University of Crete. You will explore a rich set of network architectures and thoroughly examine how several different aspects affect the accuracy of ASR. The work will be performed within the framework of advanced deep neural network architectures for various signal processing tasks including 1D and 2D signals. The focus of the post will be to perform various experiments with well-known architectures, explore and suggest modifications, process and reshape knowledge from various signal processing/classification tasks towards speech processing for the purpose of ASR. Outcomes will directly feed into improvements of ASR systems in-house working with state-of-the art ASR tasks (i.e., CHiME4, REVERB, etc) and of our industrial partners using real-life data.
The post involves travel to international conferences and project meetings with our academic and industrial partners. There will be the possibility to co-advise doctoral students and potentially other teaching opportunities.
Applicants should have a doctorate in speech signal processing area for ASR, computer science, applied mathematics or related field and ideally a strong background in deep learning and mathematics. Knowledge of deep learning systems such as Tensorflow or Theano etc and ASR systems like Kaldi are an advantage. Proficiency in computer programming in C and/or Python are expected.
Informal inquiries should be directed to Prof. Yannis Stylianou by email, yannis@csd.uoc.gr
Fixed term: In the first instance, the funding supporting the post is for two years. We are expecting project extension which will provide funding for a further 7-12 months for this post.
Interviews are expected to take place the week commencing 10th July 2017. Expected start date: September 2017, however earlier and later start dates will be considered.
 
To apply, please send detailed CV, a motivation letter and 3 major publications of yours to: yannis@csd.uoc.gr (Prof. Yannis Stylianou)

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Department of Computer Science, University of Crete, Greece

Post-doctoral Research Associate in Data Augmentation in the context of Deep Neural network ASR

(Fixed Term)

SALARY: €24000-€28000 per year

CLOSING DATE: 30 June 2017

REFERENCE: ASR2

TO APPLY: Send detailed CV, a motivation letter and 3 major publications to yannis@csd.uoc.gr

In the past few years, Deep Neural Networks (DNNs) have achieved tremendous success for many supervised machine learning tasks, including acoustic modelling for Automatic Speech Recognition (ASR). Advanced models such as Convolutional Neural Networks (CNNs) and Long Short Term Recurrent Neural Networks (LSTMs) have contributed to recent empirical breakthroughs. However, deep learning methods are quite demanding in the amount of data for training an acoustic model for ASR and as a result significant amounts of transcribed data has become available for training use. But data transcription is a quite expensive and time consuming process. On the other hand, just adding data recorded in real-world conditions puts serious constraints on the efficient training of the acoustic models. Various works on data augmentation show that word error rate (WER) can be significantly reduced if proper augmented data are processed.

This position represents an ideal opportunity to work in or move into data augmentation research area in the context of advanced deep neural networks for ASR, as it will involve collaborating widely across academia and industry, and working on one of the most pressing research areas of machine learning for the development of robust ASR systems.

Based in Heraklion Crete the post will be with Prof. Yannis Stylianou and Dr. George Kafentzis as part of the speech processing group within the Department of Computer Science at the University of Crete. You will design and develop smart approaches for spoken data augmentation for the purpose of multi-condition training of deep learning-based ASR systems. The work will be performed within the framework of advanced deep neural network architectures for various ASR tasks. The focus of the post will be to perform various experiments with spoken data generation, explore and suggest modifications, process and reshape knowledge from various signal processing for the purpose of ASR. Outcomes will directly feed into improvements of ASR systems in-house working with state-of-the art ASR tasks (i.e., AURORA-4, CHiME4, REVERB, etc) and of our industrial partners using real-life data.

The post involves travel to international conferences and project meetings with our academic and industrial partners. There will be the possibility to co-advise doctoral students and potentially other teaching opportunities.

Applicants should have a doctorate in speech signal processing area for ASR, statistical speech synthesis and voice conversion, audio signal processing, computer science, applied mathematics or related field and ideally a strong background in deep learning and mathematics. Knowledge of deep

learning systems such as Tensorflow or Theano etc and ASR systems like Kaldi are an advantage. Proficiency in computer programming in C and/or Python are expected.

Informal inquiries should be directed to Prof. Yannis Stylianou by email, yannis@csd.uoc.gr

Fixed term: In the first instance, the funding supporting the post is for two years. We are expecting project extension which will provide funding for a further 7-12 months for this post.

Interviews are expected to take place the week commencing 10th July 2017.

Expected start date: September 2017, however earlier and later start dates will be considered.

To apply, please send detailed CV, a motivation letter and 3 major publications of yours to: yannis@csd.uoc.gr (Prof. Yannis Stylianou)

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Position: 2 (W/M) researcher positions at IRCAM

Starting: September 1st, 2017

Duration: 18 months

Deadline for application: July, 1st, 2017

Offre d’emploi: 2 poste de chercheur (H/F) à l’IRCAM

Démarrage: 1er Septembre 2017

Durée: 18 mois

Date limite pour candidature: 1er Juillet 2017

IRCAM is proposing 2 researcher positions related to the European

H2020 Project ABC_Dj and Future Pulse.

The goal of the first position is to develop robust algorithms for

automatic melody extraction (AME) and use them to characterize the

dominant melodic profiles.

The goal of the second position is to develop robust machine

learning algorithms for the automatic recognition of music style/mood

in live performances.

Candidates should have

• High Skill in audio signal processing (spectral analysis, audiofeature

extraction, parameter estimation) (the candidate

should preferably hold a PHD in this field)

• High skill in machine learning (the candidate should preferably

hold a PHD in this field)

• High-skill in Matlab/Python programming, skills in C/C++

programming

• Good knowledge of Linux, Windows, Mac-OS environments

• High productivity, methodical works, excellent programming

style.

The hired Researchers will also collaborate with the development

team and participate in the project activities (evaluation of technologies, meetings,

specifications, reports)

Introduction to IRCAM:

IRCAM is a leading non-profit organization associated to Centre

Pompidou, dedicated to music production, R&D and education in

sound and music technologies. It hosts composers, researchers and

students from many countries cooperating in contemporary music

production, scientific and applied research. The main topics

addressed in its R&D department include acoustics, audio signal

processing, computer music, interaction technologies and

musicology. Ircam is located in the centre of Paris near the Centre

Pompidou, at 1, Place Igor Stravinsky 75004 Paris.

Salary:

According to background and experience

Applications:

Please send an application letter with the reference 201706RES

together with your resume and any suitable information addressing

the above issues preferably by email to: peeters at ircam dot fr with

cc to vinet at ircam dot fr, roebel at Ircam dot fr.

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Proposition de thèse CIFRE en Informatique, traitement automatique du langage naturel

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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].

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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 videos 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 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 Sales Manager, the Language Resources Project Manager ? Junior will be in charge of the identification of Language Resources (LRs) and the negotiation of rights in relation with their distribution.

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.
• LR Packaging and Archiving.
• Designing and evaluating workflows for IPR clearance in the digital environment.

Profile:

• Master?s degree or equivalent in Law and Computer science, with an awareness of Intellectual Property Rights and Data Protection issues in the digital environment.
• The ideal candidate will have experience in computational linguistics, information science, knowledge management or similar fields.
• 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.
• 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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nceThèse de doctorat en traitement de la parole Parkinsonienne à INRIA Bordeaux

Sujet : Traitement non-linéaire de la parole pour l'analyse et la classification de voix

Parkinsoniennes

Contexte scientifique :

La maladie de Parkinson (MP) est la maladie neurodégénerative la plus répandue après la maladie

d'Alzheimer. Elle touche 1.5% de la population âgée de plus de 65 ans et 143000 français. L'atrophie

multi-systématisée (AMS) est une maladie neurodégénérative rare et sporadique d'évolution

progressive et d’étiologie inconnue. Elle a une prévalence de 2 à 5/100000 et n'a pas de traitement

effectif. AMS appartient au groupe des troubles parkinsoniens atypiques et est responsable d’un

pronostic péjoratif. Dans les premiers stades de la maladie, les symptômes de MP et AMS sont très

similaires, surtout pour AMS-P où le syndrome parkinsonien prédomine. Le diagnostic différentiel

entre AMP-P et MP peut être très difficile dans les stades précoces de la maladie, tandis que la certitude

de diagnostic précoce est important pour le patient en raison du pronostic divergent. En effet, malgré

des efforts récents, aucun marqueur objectif valide n'est actuellement disponible pour guider le

clinicien dans ce diagnostic différentiel. La nécessité de ces marqueurs est donc très élevé dans la

communauté de la neurologie, en particulier compte tenu de la gravité du pronostic de AMS-P.

Les troubles de la parole et de la voix, communément appelés dysarthrie [1,2], dans la maladie de

Parkinson sont un marqueur clinique qui coïncide avec une déficience motrice et l'apparition d'une

déficience cognitive. Comme les patients MP, en fonction des zones du cerveau qui sont endommagées,

les personnes souffrant d'AMS peuvent également avoir des troubles de la parole: difficultés

d'articulation, rythme staccato, voix grinçante ou silencieuse. La dysarthrie dans l'AMS est plus sévère

et plus précoce dans le sens où elle nécessite plus de rééducation précoce par rapport à la MP.

Comme les troubles de la parole sont un symptôme précoce commun aux deux maladies et d'origine

différente. Notre approche consiste à utiliser la dysarthrie, grâce à un traitement numérique des

enregistrements vocaux des patients, comme un vecteur pour l'aide au diagnostic différentiel entre MP

et AMS-P dans les stades précoces de la maladie.

Objectif de la thèse :

Les voix pathologiques, telles que la MP et la MSA, présentent généralement une forte non-linéarité et

une turbulence élevée. Les phénomènes non-linéaires/turbulents ne sont pas naturellement bien décrits

par le traitement linéaire du signal. Ce dernier règle cependant actuellement sur la technologie de la

parole. Ainsi, du point de vue méthodologique, l'objectif de cette thèse est d'étudier la parole

Parkinsonienne dans le cadre des signaux et systèmes non linéaires et turbulents [3] . Ce cadre est en

effet mieux adapté à l'analyse de la gamme des phénomènes non linéaires et turbulents observés dans

les voix pathologiques en général, et dans la voix MP et MSA en particulier. Nous adopterons

notamment une approche basée sur de nouveaux algorithmes d'analyse non-linéaire de la parole

récemment développés dans l'équipe Gestation [4]. L'objectif est d'extraire les caractéristiques de la

parole pertinentes pour concevoir de nouvelles mesures de dysarthrie qui permettent une discrimination

précise entre les voix de MP et de MSA. Cela nécessitera également l'utilisation de méthodes

d'apprentissage statistique (Machine learning) afin de développer des classificateurs robustes (pour

discriminer les voix de MP et MSA) et d'établir des correspondances (régression) entre des mesures de

la parole et les scores cliniques standard quantifiant la sévérité de la maladie.

Les partenaires cliniques de ce projet sont des centres du CHU-Bordeaux et du CHU-Toulouse de

renommée internationale sur MP et AMS. Les partenaires académiques sont l'équipe Samova de l’IRIT,

qui a une grande expertise en traitement (linéaire) de la parole, et l'Institut Mathématique de Toulouse

(IMT) pour les aspects Machine learning.

Le doctorant participera ainsi activement à la collecte de données, en coordination avec les neurologues

et phoniatres du CHU-Bordeaux et CHU-Toulouse. Ces données consisteront en l'enregistrement des

voix des patients à l'aide d'un enregistreur numérique et du dispositif EVA2 (http://www.sqlab.fr/), ainsi

que de signaux électroglottographiques (EGG).

Références:

[1] Freed, D. Motor speech disorders. Thomson Learning Eds. 2000.

[2] Auzou, P.; Rolland, V.; Pinto, S., Ozsancak C. (eds.). Les dysarthries. Editions Solal. 2007.

[3] Kantz, H. and T. Schreiber, Nonlinear time series analysis. 2nd ed. 2004, Cambridge; New York: Cambridge

University Press.

[4] PhD thesis of Vahid Khanagha. GeoStat team, INRIA Bordeaux-Sud Ouest. January 2013.

http://geostat.bordeaux.inria.fr/images/vahid%20khanagha%204737.pdf

Directeur : Dr. Khalid Daoudi, équipe Gestat (khalid.daoudi@inria.fr).

Lieu : INRIA- Bordeaux Sud Ouest (http://www.inria.fr/bordeaux). Bordeaux, France.

Financement : Projet ANR (Voice4PD-MSA)

Début de la thèse : entre Le 1er Octobre et le 31 décembre 2017

Durée : 3 ans

Rémunération : ~1600€ net/mois, incluant la couverture sociale et médicale.

Compétences requises : De très bonnes connaissances en traitement de la parole/signal ainsi qu'en

programmation C++/Python et Matlab sont nécessaires. Des connaissances en apprentissage statistique

(Machine learning) seraient un grand plus.

Les candidatures doivent être adressées à khalid.daoudi@inria.fr

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eurosPost-doc à Paris et Saclay : Apprentissage semi-supervisé et apprentissage profond pour une mesure de l'expérience émotionnelle du client dans les interactions orales

[1] Telecom ParisTech, 46 rue Barrault, 75013 Paris

[2] EDF Lab Paris Saclay, 7 boulevard Gaspard Monge 91120 Palaiseau

Durée :  1 an

Début :  Novembre 2017

Salaire : en fonction de l'expérience et à partir de 2300 euros/mois

*Description du sujet de post-doctorat*

Avec l'engouement récent du Big Data pour le Feel data, EDF souhaite développer des méthodes d'analyse automatique de l'expérience émotionnelle du client dans ses interactions orales. Les interactions orales considérées sont les données des centres d'appels et données d'interaction avec des assistants virtuels vocaux (de type Alexa, Siri). L'objectif du post-doctorat est de mettre en place desméthodes d'apprentissage semi-supervisées, combinées à de l'apprentissage profond (deep learning) pour l'analyse automatique de l'expérience émotionnelle du client. Les méthodes reposeront sur des caractéristiques (features) linguistiques et acoustiques extraites des interactions orales.

Le chercheur post-doctorant prendra part à une collaboration entre EDF Lab et Telecom-ParisTech et son travail de recherche reposera sur les étapes suivantes :

- la mise en place de schéma d?annotation de l?expérience émotionnelle de l?utilisateur sur les données collectées à EDF Lab (données des centres d'appels et données d'interaction avec des assistants virtuels vocaux (de type Alexa, Siri)

- l?extraction d?indices acoustiques caractéristiques des réalisations non verbales de l?expérience émotionnelle de l?utilisateur

- l?extraction d?indices linguistiques caractéristiques des réalisations verbales de l?expérience émotionnelle de l?utilisateur

-  la mise en place de stratégies d?apprentissage permettant de mixer des approches non supervisées et des approches d?apprentissage profond

Le post-doc aura lieu au sein des deux centres de recherche : EDFLab [2] et Telecom-Paristech (département IDS image and signal processing department of Telecom ParisTech [1], équipe S2a, thème Social computing).

* Profil du candidat*

Le candidat devra posséder a minima les compétences suivantes :

?    un diplôme de doctorat

?   des recherches et publications dans au moins l?une des thématiques suivantes : machine learning, traitement de la parole, affective computing. Traitement automatique des langues

?    d?excellentes compétences en programmation  (avec une préférence pour le python)

?    excellente maîtrise du français et bonne maîtrise de l?anglais

Les compétences ci-dessous, seront également un atout :

?        apprentissage semi-supervisé

?        Deep learning

?        analyse acoustique des émotions

-- Informations pratiques

Lieu du post-doc: Paris (Telecom-ParisTech) et Palaiseau (EDF Lab Paris-Saclay)

Encadrement : Delphine Lagarde, Aurélie Dano (EDF Lab) et Chloé Clavel (Telecom-ParisTech)

-- Comment candidater :

Les candidatures sont à envoyer à Chloé Clavel (chloe.clavel@telecom-paristech.fr)

Elles doivent être compilées ** en un seul fichier pdf ** et inclure :

?    Un CV complet et détaillé incluant la liste des publications

?    Une lettre de motivation spécifique au sujet du post-doc

?   Les noms et les adresses de 2 référents.

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

[2]htttps://www.edf.fr/groupe-edf/qui-sommes-nous/activites/recherche-et-developpement/nos-centres-de-recherche/le-centre-de-recherche-edf-lab-paris-saclay-souffle-sa-premiere-bougie  

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Vocapia Research is hiring an R&D Engineer/Scientist, to build and improve multilingual language processing systems relying on machine learning techniques. We are seeking candidates with substantial programming experience who are able to carry out careful experimental work, paying attention to details. We are looking for highly-motivated, goal-driven individuals who also desire to be team players.

Main qualifications

• Master's, PhD or Engineering degree in Computer Science or Electrical Engineering
• Experience in language processing, speech recognition or machine learning
• Strong programming skills using C/C++ and scripting languages in a UNIX/Linux environment
• Good knowledge of written and spoken English. Fluency in one or more other languages is a strong plus (in particular Arabic, Dutch, German, Italian, Japanese, Mandarin, Polish, Portuguese, Romanian, Russian, Spanish and Turkish)

Preference will be given to candidates who have experience in speech and language processing.

Location: Orsay, France (about 25km out of Paris )

To apply please submit your CV by email (including the job reference and your contact information) to recruit(at)vocapia.com or directly fill in the online application form (http://www.vocapia.com/applyforjob.html?VR1706IRD)

PDF or PS file, please.

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Intelligent Voice Ltd, London City, UK
Postdoctoral researcher in Cryptography

In the framework of a H2020 program of the European Commission, Intelligent Voice Ltd is receiving financial support to hire a postdoctoral researcher for one year on the following topic :

The cloud offers an ideal opportunity for storing large volumes of data. However, the storage of sensitive data such as speech in plain text format on the cloud is not permitted in many industry sectors such as finance, health care etc. Hence speech data should be encrypted before storage on the cloud, and because it contains biometric identifiers it must remain encrypted. The challenge then is to search over large amounts of encrypted speech and return encrypted search results that can be decrypted by the user only. Intelligent Voice are providers of the world's fastest speech to text engine, and we are looking for a talented researcher in semantic security and searchable encryption to join our research team. This post builds on existing research within Intelligent Voice on Searchable and Homomorphic cryptographic protocols for speech processing.

Applicants should have already completed, or be close to completing, a PhD in computer science, mathematics, or a related discipline. Applicants should have an excellent research track record demonstrated by publications at major cryptography/security venues, and should have significant experience in the design and deployment of cryptographic protocols.

To apply please send your CV (with publication list), a 1-page cover letter, and the names of at least two people who can provide reference letters (e-mail).

Contact: Gérard Chollet, Head of Research, Intelligent Voice Ltd

St Clare House, 30-33 Minories, London EC3N 1BP

gerard.chollet(at)intelligentvoice.com

Phone: +44 20 3627 2670

More Information: http://www.intelligentvoice.com/https://www.slideshare.net/cholletge/ppsp-icassp17v10-72961572

Closing Date for Applications: 2017-08-31

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AI – NLP Researcher
 
 
 
COMPANY: SPARTED is an innovative and disruptive startup that is changing the way people learn. We offer companies and organizations a unique and scalable game platform for micro learning on mobile devices. www.sparted.com
 
MISSION:  In the context of ambitious and strategic project targeting to automatically generate questions from descriptive texts in a variety of semantical contexts, the mission consists in: • Establishing a state of the art of capabilities of NLP regarding the project • Designing and identifying the main milestones of a long-term research plan working collaboratively with a research lab  • Contributing to the development of proofs of concepts with our team • Spreading Machine Learning knowledge inside the team and train our engineers to Natural Language Processing specificities • Designing and administrating flexible, scalable datasets • Contributing to the company vision
 
REQUIRED SKILLS: • Depth and breadth of knowledge in Machine Learning and NLP • Experience solving analytical problems using quantitative approaches • Ability to manipulate and analyze data from varying sources • Knowledge in some programming language
PROFILE: You have or you’re about to defend a PhD in Machine learning, AI, Applied Mathematics, Data Science, Statistics , Computer Science or related technical field with a strong focus on Natural
Language Processing and related technologies such as pattern recognition, sequence-to-sequence models, word2vec, etc. You like taking up challenges, teamwork and building awesome products.
 
BONUS SKILLS THAT WOULD BE GREAT: • French language  • Experience in Text Mining • Beer pong master • Demonstrated experience with Natural Language Technologies and engines  • Familiarity with Semantic Technologies • White Russian expertise • Extreme skiing or Wingsuit practice
 
REMUNERATION: Depending on your status, talent and experience (€ 30K - xxK) Internship, PhD project (CIFRE) or other
 
LOCATION: The position is based in Paris, avenue Kléber, next to the Place de l’Etoile, in our so cool top floor premises with an exceptional view on Paris and the Eiffel tower.
 
JOIN THE FUN DISRUPTION: SPARTED is at war. The fun rebellion is running against the empire of boredom. SPARTED is strengthening, growing and completing its forces by recruiting superheroes, in addition to an exceptional 20 people team of world-class best developers, project managers, designers and other performers.
 
Fun disruptors are men and women, enthusiastic personalities involved in the future, smart cookies and bold people, wanting to continuously evolve, improve themselves and change the world. If you’re made of the right stuff, this position is the opportunity to join a daring project in a successful start-up with a strong identity and mindset, with great career prospects.
 
APPLICATION: Say us hello at start@sparted.com +33 6 52 14 86 9

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Three job offers at Laboratoire de Phonétique et Phonologie, Paris, France (1phD and 2 postdocs)

In the context of the MoSpeeDi project, funded by the FNS and run in collaboration with the University of Geneva, the HUG and IDIAP,  the Laboratoire de Phonétique et Phonologie* (LPP ? CNRS/Sorbonne Nouvelle) in Paris is offering 3 positions (1 phD and 2 postdocs) starting November 2017 or later.

The general goal of the project is to better understand the processes and representations at play during speech production, focusing on the latest stages of the process where an encoded linguistic message is transformed into articulated speech. At the interface between linguistic and motor processes, these stages are also associated with different breakdowns considered as Speech Motor Disorders (dysarthria and apraxia of speech).

Articulatory, acoustic and speech behaviour data will be experimentally collected and analysed for both healthy speakers and speakers with speech motor disorders in order to (a) improve the characterization of phonetic speech planning and motor speech programming, (b) to identify phonetic and speech behavior markers of these processes, and (c) to better isolate and classify speech alterations in speech motor disorders. 

Within this Swiss-French collaborative project, the LPP is recruiting 1 doctoral student and 2 post-docs to join the team under the supervision of Cécile Fougeron (DR CNRS) and in close collaboration with Simone Falk (MC Sorbonne Nouvelle), and Leonardo Lancia (CR CNRS). See job description and application procedure below.

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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


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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Amongst several openings at Idiap in general, we have *three* post-doctoral positions in
the areas of multilingual speech processing and cross-lingual indexing:
 http://www.idiap.ch/en/join-us/job-opportunities
They are funded by EU and US projects, so there will be plenty of opportunity to
collaborate with partners in the EU and US.

Idiap has well established speech and NLP groups.  We are located in a wine region in the
Swiss Alps, a couple of hours out of Geneva.  The lab functions in English, the locality
in French.

--

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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:
https://sjobs.brassring.com/TGWEbHost/jobdetails.aspx?partnerid=25483&siteid=5291&AReq=3499BR

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 https://sjobs.brassring.com/TGWEbHost/jobdetails.aspx?partnerid=25483&siteid=5291&AReq=3499BR. 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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