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

developing acoustic and 

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

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

commercialization of speech recognition

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

in and/or demonstrate 

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

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

topics including 

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

o Signal Processing/Pattern Recognition 

o Probability theory 

o Bayesian inference 

o Machine learning and related topics 

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

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

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

o Kaldi, KenLM, OpenFST, and HTS 

o Theano, PDNN, pyTorch, TensorFlow 

• Operating Systems: Unix/Linux/Mac OS 
 
 
 
 

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

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

amongst other benefits. 

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

topics including 

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

o Signal Processing/Pattern Recognition 

o Probability theory o Bayesian inference 

o Machine learning and related topics 

• Strong software development skills 

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

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

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

o Festival, HTK, and HTS 

o Theano, PDNN, pyTorch, TensorFlow 

• Operating Systems: Unix/Linux/Mac OS 
 
 
 
 

 1 The Green Richmond, TW9 1PL UK 

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

amongst other benefits.

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



Maëva Garnier

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

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

Location: Delft University of Technology, The Netherlands

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

Project Description:

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

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

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

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

Job requirements:

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

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

Institution:

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

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

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

Application Procedure:

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

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

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

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

Détails de l'offre :

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Adaptation des réseaux de neurones profonds pour les systèmes 

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

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

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

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

que la précédente. 

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

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

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

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

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

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

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

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

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

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

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

Speech and Audio Processing (TASP), 1994. 

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

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

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

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

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

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

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

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

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

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

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

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

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

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Internship and PhD position in machine learning for multimodal engagement analysis

in human-robot interactions (HRI)

Telecom ParisTech [1],  LTCI lab [2]

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

Salary: according to background and experience

*Position description*

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

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

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

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

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

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

* Candidate profile*

As a minimum requirement, the successful candidate will have:

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

?    Excellent programming skills (preferably in Python)

?    Good command of English

The ideal candidate will also (optionally) have:

?    Knowledge in deep learning techniques

-- More about the position

?    Place of work: Paris, France

?    For more information about Télécom ParisTech see [1]

-- How to apply

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

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

?    A complete and detailed curriculum vitae

?    A letter of motivation

?    Academic records of the last two years

?    The names and addresses of two referees

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

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

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

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

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

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

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

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

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

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

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

A ce titre, vous serez en charge de :

1 – Effectuer de la Recherche scientifique et technologique

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

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

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

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

-        Encadrer des stagiaires et à terme des doctorants ;

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

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

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

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

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

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

3 – Réaliser des partenariats

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

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

4 – Collaborer au management fonctionnel

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

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

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

Profil :

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

Complété de compétences en : 

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

-        Bonne pratique en recherche académique et/ou industrielle ;

-        Pratique en publications scientifiques ;

-        Bonne connaissance et pratique de projets collaboratifs ;

-        Connaissance du paysage audiovisuel français ;

-        Connaissance du monde académique ;

-        Maîtrise des outils bureautiques ;

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

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

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

Modalités du poste :

-        Contrat : CDI

-        Statut : Cadre

-        Poste à pourvoir : au plus vite

-        Salaire : selon expérience

-        Clôture de la consultation : 31 janvier 2018

-        Contact : jcarrive@ina.fr

-        Localisation géographique : Bry S/Marne (94)

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

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

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

 

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

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

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

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

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

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

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

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


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

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

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

Description

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

We envisage three related research threads:

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

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

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

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

Profile

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

Timescale

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

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

We are especially interested in adding faculty in these preferred areas:    

(1) Wearable, contextually-aware and personalized interfaces

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

Requirements:

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

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

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

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

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

?    Strong interpersonal, teamwork, communication and writing skills

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Please note the following important dates:

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

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

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

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

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

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

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

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

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


- Speech Processing

- Natural Language Understanding

- Conversational Systems

- Machine Learning

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


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

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

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

FELLOWSHIP

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

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

DEADLINES

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

REQUIREMENTS

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

HOW TO APPLY

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

Email: sisl-jobs@disi.unitn.it


For more info:

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

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

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


Information Engineering and Computer Science Department (DISI)

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

University of Trento

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

University of Trento is an equal opportunity employer.

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Post-doctoral researcher at Idiap Research  Institute. 

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

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

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

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Post Doctoral Position (12 months)

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

_______________________________________

- Location:INRIA Nancy Grand Est research center, France

- Research theme: PERCEPTION, COGNITION, INTERACTION

- Project-team: Multispeech

- Scientific Context:

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

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

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

- Missions:

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

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

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

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

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

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

- Bibliography

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

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

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

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

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

- Additional information:

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

Additional links : Ecole Doctorale IAEM Lorraine

Deadline to apply: June 6^th

Selection results: end of June

Duration :12 of months.

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

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

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

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

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

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

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

Help and benefits:

• Possibility of free French courses

• Help for finding housing

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

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

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

- Research theme:Perception, Cognition, Interaction

- Project-team: Multispeech

- Scientific Context:

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

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

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

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

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

- Missions:

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

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

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

- Bibliography:

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

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

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

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

- Additional information:

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

Additional links: Ecole Doctorale IAEM Lorraine

Duration: 3 years

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

Deadline to apply : May 1^st 2018

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

• CV

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

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

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

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

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

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Junior Linguist [French]

Job Title:

Junior Linguist [French]

Linguistic Field(s):

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

Location:

Paris, France

Job description:

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

• Providing phonetic/phonemic transcription of lexicon entries

• Analyzing acoustic data to evaluate speech synthesis

• Annotating and reviewing linguistic data

• Labeling text for disambiguation, expansion, and text normalization

• Annotating lexicon entries according to guidelines

• Evaluating current system outputs

• Deriving NLP data for new and on-going projects

• Be able to work independently with confidence and little oversight

Minimum Requirements:

• Native speaker of French and fluent in English

• Extensive knowledge of phonetic/phonemic transcriptions

• Familiarity with TTS tools and techniques

• Experience in annotation work

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

• Excellent oral and written communication skills

• Attention to detail and good organizational skills

Desired Skills:

• Degree in Linguistics or Computational Linguistics or Speech processing

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

• Keen interest in technology and computer-literate

• Listening Skills

• Fast and Accurate Keyboard Typing Skills

• Familiarity with Transcription Software

• Editing, Grammar Check and Proofing Skills

• Research Skills

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

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Postdoctoral Research Scientist: Computational Linguistics

We invite applications for an interdisciplinary postdoctoral position with specialization in computational linguistics and/or technical or scientific methods in language science at Rochester Institute of Technology (RIT), in Rochester, NY. This is a one-year position with opportunity for renewal. The applicant should demonstrate a fit with our commitment to collaborate with colleagues across the university on research initiatives in Personalized Healthcare Technology. In addition to engaging in research projects, the right candidate will be able to teach a total of two courses per year - one course each in the College of Liberal Arts and the Golisano College of Computing and Information Sciences at RIT. The teaching assignment may be Computer Science Principles, Introduction to Language Science, Language Technology, Introduction to Natural Language Processing, Science and Analytics of Speech (acoustic and experimental phonetics), Spoken Language Processing (automatic speech recognition and text-to-speech synthesis), Seminar in Computational Linguistics, or another course depending on background.

Required Minimum Qualifications

- PhD., with training in Computational Linguistics, Linguistics, or an allied field

- Advanced graduate coursework in computational linguistics (natural language processing or speech processing), linguistics, or language science broadly

- Publication record and plan for research and grant seeking activities

- Ability to contribute in meaningful ways to our commitment to cultural diversity, pluralism, and individual differences

Required Application Documents

Cover Letter, Curriculum Vitae or Resume, List of References, Research Statement

How To Apply

Please apply at: http://careers.rit.edu/staff. Click the link for search openings and in the keyword search field, enter the title of the position or 3599BR.

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A Postdoctoral Research Associate (PDRA) position is available in English Language and Linguistics at the University of Kent. We are looking for an enthusiastic candidate to join for our interdisciplinary team working on a project funded by the Leverhulme Trust - ?Does Language Have Groove? Sensorimotor Synchronisation for the Study of Linguistic Rhythm?. The project brings together expertise from phonetics, cognitive and movement sciences, and involves a collaboration between the University of Kent (UK) and the University of Montreal (Canada), in particular the International Laboratory for Brain, Music and Sound Research (BRAMS). The post holder will be based at Kent in Canterbury, with opportunities to travel to collaborative meetings and conferences.

This project aims to resolve current controversies surrounding rhythmic properties of language. Using paradigms based on sensorimotor synchronisation and rhythmic movement to cross-linguistic materials, we will develop new approaches to the study of linguistic rhythm. The PDRA will have strong computational skills and expertise in data analyses and modelling. S/he will be responsible for collecting and analysing tapping and perception data, for disseminating the project?s findings to academic and non-academic audiences, and writing up the results for publication.

The successful candidate must have a PhD in Phonetics, Experimental Psychology, Cognitive Science, Computing, Movement Sciences or related disciplines. Excellent programming skills in MATLAB/R environments as well as expertise in experimental design and statistical methods (e.g., multivariate statistics, linear mixed models, time-series analyses) are required. A publication record (commensurate with the applicant?s career stage), knowledge of non-linear modelling advanced techniques and experience working with different speech perception paradigms are highly desirable. The candidate should enjoy working in an interdisciplinary environment and be interested in working with speakers from typologically diverse language backgrounds. Language knowledge in addition to English (French, Italian and/or non-European languages) are a plus.

The required application documents include (1) a cover letter outlining the candidate?s background and suitability for the post and (2) a CV with a list of publications and contact details of three academic referees who are available to provide a reference letter for the shortlisted candidates prior to the interview date.
?    Start date for applications: 24 January 2018
?    Closing date for applications: 26 February 2018
?    Interviews are to be held: 29 March 2018
?    Start date of the post: 1 May 2018
Please use this link to view the full job description and also to apply for this post. If you require further information regarding the application process please contact The Resourcing Team on jobs@kent.ac.uk quoting ref number: HUM0834. For informal enquiries about the post, please contact Dr Tamara Rathcke (t.v.rathcke@kent.ac.uk) +44 1227 826540.

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 The department of Communications Engineering at Paderborn University, Faculty of Electrical Engineering, Informatics and Mathematics, offers a position as  
Post-Doctoral Researcher (pay scale 13 TV-L)
at full time employment (100 %). The position is according to the German Wissenschaftszeitvertragsgesetz (WissZeitVG) and aims for scientific qualification in the area of project management and original research. It is temporary for 1.5 years, which is considered suitable for the qualification aim. An extension is, in principle, possible.
The project: Your work will be concerned with signal processing and machine learning for wireless acoustic sensor networks. The research is carried out in the context of a multidisciplinary and multi-site collaborative research initiative. 
 
About us: We are a highly motivated research group working on cutting-edge techniques for robust acquisition and processing of speech and audio, such as enhancement, beamforming, source separation, recognition and acoustic scene understanding. We have strong links to both national and international research groups. .
About you:  You hold a PhD in Electrical Engineering, Computer Science or a closely related field  You gained thorough and extensive knowledge in the fields of signal processing and machine learning for audio or speech  You have a strong publication record demonstrating innovative research achievements  You have excellent programming skills
 
Applications of women are particularly welcome and, in case of equal qualifications and experiences, will receive preferential treatment according to the North RhineWestphalian Equal Opportunities Act (LGG), unless there are preponderant reasons to give preference to another applicant. Part-time employment is, in principle, possible. Applications from disabled people with appropriate suitability are explicitly welcome. This also applies to people with equal opportunities in accordance with the German social law SGB IX.
Information about the Department of Communications Engineering can be found at http://ei.uni-paderborn.de/nt/ 
Please send your application including letter of motivation, research profile, CV, certificates, list of publications, and contact data for reference letters by mail citing the  reference  number 3291, not later than 31 March 2018, to: 
Prof. Dr. Reinhold Häb-Umbach Fachgebiet Nachrichtentechnik Universität Paderborn Warburger Str. 100 33098 Paderborn GERMANY (haeb@nt.uni-paderborn.de)

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Position:  1 (W/M) researcher positions at IRCAM    Starting:    April 1st, 2018 Duration:    12 months

Deadline for application: March, 15th, 2018 
 
 Position description 201802UMGRES:
 IRCAM is looking for a researcher for the development of music content analysis technologies (such as tempo, chord, structure, auto-tagging) in the framework of a technology transfer with Universal Music Group.
 
Required profile: • Very high Skill in audio signal processing (spectral analysis, audio-feature extraction, parameter estimation) (the candidate should preferably hold a PHD in this field) • Very high skill in machine learning (SVM, ConvNet) (the candidate should preferably hold a PHD in this field)  • High skill in distributed computing • High-skill in Matlab and Python programming, skills in C/C++ programming  • Good knowledge of UNIX environments (GNU-Linux ou MacOSX)  • 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 201802UMGRES 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. 
 
 
 

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Postdoctoral Researcher

(computational linguistics or computer science)

Models of Intercomprehension in Speech and Language

The Language Science and Technology department at Saarland University seeks to fill a postdoctoral position. Applications are invited from individuals with research expertise in any field related to speech science and speech technology. Our research project is concerned with the analysis of cross-lingual mutual intelligibility between Slavic languages. It studies the auditory-perceptual intercomprehension of Slavic languages based on analyses of the acoustic, phonetic and phonological structure of spoken utterances. This line of investigation will be complemented by using adaptation techniques established in speech synthesis and recognition to measure the distance between languages. In addition, similarity will be determined on the level of complete utterances.

The postdoc will join a vibrant community of speech and language researchers at Saarland University whose expertise spans areas such as computational linguistics, psycholinguistics, language and speech technology, speech science, theoretical and corpus linguistics, computer science, and psychology.

Requirements: The successful candidate should have a Ph.D./Master's in Computer Science, Computational Linguistics, or a related discipline, with a strong background in speech science and speech technology, in particular TTS and ASR. Strong programming skills are essential. A good command of English is mandatory. Working knowledge of German is desirable but not a prerequisite. Candidates must have completed their Ph.D. by the time of the appointment.

The position is a full position (100%) on the German E13 scale and subject to the final approval by the funding agency. Starting dates can be between July and October, 2018. The appointment will be for between one and four years.

About the department: The department of Language Science and Technology is one of the leading departments in the speech and language area in Europe. The flagship project at the moment is the CRC on Information Density and Linguistic Encoding. Furthermore, the department is involved in the cluster of excellence Multimodal Computing and Interaction. It also runs a significant number of European and nationally funded projects. In total it has seven faculty and around 50 postdoctoral researchers and PhD students.

How to apply: Please send us: (1) a letter of motivation, (2) your CV, (3) your transcripts, (4) a list of publications, and (5) the names and contact information of at least two references, as a single PDF or a link to a PDF if the file size is more than 3 MB.

Please apply by April 3rd, 2018.

Contacts: If you are interested in the project, please send an email to Bernd Möbius (moebius@coli.uni-saarland.de) and Dietrich Klakow (dietrich.klakow@lsv.uni-saarland.de).

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POSTDOCTORAL FELLOW POSITION

Applications are invited for a 12-month full-time (with possible 12-month extension) Postdoctoral Position in cognitive neuroscience in Lyon, to collect and analyze fMRI data on language processing. The post-doc is part of an exciting new project, which is a collaboration between Drs Alice Roy and Véronique Boulenger from the Laboratory Dynamics of Language (CNRS), and Dr Claudio Brozzoli from the Lyon Neuroscience Research Centre (INSERM).

The project lies in the context of embodied cognition theories and aims at uncovering the functional role of the motor system in second language processing. It will examine, using fMRI, the dynamics of cortical activation in motor regions before and after phonological training in a foreign language.

The project will be conducted in Lyon, a vibrant and stimulating neuroscience environment and a culturally rich city life, ideally located just an hour away from the Alpes, 2 hours from Paris and an hour and a half from Marseille and the Mediterranean sea (by train).

Key requirements for the candidates:

The ideal candidate will have a PhD in neuroscience, cognitive sciences or a related field and will have substantial experience in fMRI imaging analyses (e.g. SPM, connectivity analysis, resting state) and good programming skills (MATLAB). A background in speech and language is required.

Applications in the form of a cover letter with statement of research interests and a CV with full publication list should be sent by email to alice.roy@cnrs.fr and veronique.boulenger@cnrs.fr, with cc to claudio.brozzoli@inserm.fr.

Applicants from outside the European Union are welcome but they must qualify for a valid visa. French speaking is not a requirement (although it is an asset) as long as the English language is mastered.

Starting date: 2018 ? please contact us for further information.

Net salary: ~2000 ? / month

Applications will be considered until the position is filled.

Please feel free to forward this announcement to colleagues and students who could be interested in this position.

http://www.ddl.ish-lyon.cnrs.fr/equipes/index.asp?Langue=EN&Equipe=7&Page=Presentation&

--

Véronique Boulenger

Chargée de Recherche CNRS

Laboratoire Dynamique Du Langage

UMR5596 CNRS/Université de Lyon

04.72.72.79.24

veronique.boulenger@cnrs.fr

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RESEARCH LINGUIST
 
Come join us and build Personal Artificial Intelligence (PAI) -- intelligent 3D avatars that look, sound, and behave like the individual user!
 ObEN is an artificial intelligence company developing a decentralized AI platform for Personal AI (PAI). Founded in 2014, ObEN is a K11, Tencent, Softbank Ventures Korea and HTC Vive X portfolio company.
 
As a Research Linguist, you will collaborate with other scientists who are experts in speech engineering, natural language processing, and computer vision. You will be working on a variety of tasks to improve technologies for speech synthesis, speech recognition, visual speech, and natural language processing. 
 
The tasks include:

● Design material and procedures to collect spoken and written language data;

● Design schemas and label/tag sets to annotate recordings and text with phonetic, prosodic, semantic, and syntactic features;

● Design methods and protocols to ensure the quality of linguistic data and annotations;

● Design perceptual or linguistic tests to evaluate the performance of speech and language systems;

● Contribute to the formalization of speech and language models by offering linguistic knowledge, identifying issues and providing solutions. 
 
Basic qualifications:

● Masters or higher degree in Linguistics or a closely-related field

● Specialization in Phonetics or Phonology

● Native or near-native proficiency in Japanese or Korean

● Ability to use programming scripts
 
Preferred qualifications:

● Knowledge of scripting languages, e.g., Python

● Background in Psychology/Psycholinguistics

● Willingness to accept reprioritization as necessary
 
 
Contact: pierre@oben.com

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SPEECH RESEARCH SCIENTIST (ASR)
 
Come join us and build Personal Artificial Intelligence (PAI) -- intelligent 3D avatars that look, sound, and behave like the individual user!
 ObEN is an artificial intelligence company developing a decentralized AI platform for Personal AI (PAI). Founded in 2014, ObEN is a K11, Tencent, Softbank Ventures Korea and HTC Vive X portfolio company.
 
As an ASR Research Scientist, you’ll be working on developing tools to automate speech data               acquisition and selection from diverse sources of data for the training of ObEN’s speech              technology components.
 
Responsibilities:
 
● Develop and extend ObEN’s proprietary ASR systems for different languages (English, Chinese, Korean, Japanese), in view of improving the robustness against environmental and channel distortion;

● Develop long (>1h) speech-text alignment systems;

● Develop lyrics-singing voice alignment systems;

● Develop tools and measures for data selection (confidence scores, acoustic measures);

● Develop tools for metadata extraction from speech and text (e.g: emotion, speakerID, etc).
 
Requirements:

● PhD with strong research experience in ASR demonstrated by publications in top Speech Journals and Conferences (ICASSP, Interspeech, ASRU, etc.);

● Experience with robust ASR,  long speech-text alignment, lightly supervised approaches and confidence measures computation; ● Fluent in Python and C++, excellent knowledge of Kaldi;

● Strong machine learning background and familiar with standard statistical modeling techniques applied to speech;

● Good knowledge of deep learning packages (Tensorflow, Theano, Keras, etc).
 
 
Contact: pierre@oben.com

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SPEECH RESEARCH SCIENTIST (Prosody Modeling)
 
Come join us and build Personal Artificial Intelligence (PAI) -- intelligent 3D avatars that look, sound, and behave like the individual user!
 ObEN is an artificial intelligence company developing a decentralized AI platform for Personal AI (PAI). Founded in 2014, ObEN is a K11, Tencent, Softbank Ventures Korea and HTC Vive X portfolio company.
 
As a Speech Research Scientist focusing on Prosody Modeling, you will be working on developing new prosody models for different languages (Chinese, English, Japanese, Korean) to improve the naturalness and the similarity of the synthesized voice and to allow a better control of its expressivity. 
 
Responsibilities:

● Develop new prosody model for different languages, adaptable using a small amount of data;

● Develop generic prosodic models for different expressivity which can be applied to any voice;

● Develop sentiment analysis algorithms to control expressivity from text input.  

Requirements:

● PhD with strong experience in Prosody Modeling for Speech Synthesis demonstrated by publications in top Speech Journals and Conferences (Speech prosody, Icassp, Interspeech, etc);

● Strong implementation skills and general knowledge in ML;

● Fluent in Python and C++, and good knowledge of deep learning packages;

● Familiarity with linguistic phonetics;

● Knowledge of basic digital signal processing techniques for audio.
 
 
Contact: pierre@oben.com

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SPEECH RESEARCH SCIENTIST (Singing Voice Synthesis)
 
Come join us and build Personal Artificial Intelligence (PAI) -- intelligent 3D avatars that look, sound, and behave like the individual user!
 ObEN is an artificial intelligence company developing a decentralized AI platform for Personal AI (PAI). Founded in 2014, ObEN is a K11, Tencent, Softbank Ventures Korea and HTC Vive X portfolio company.
 
As a Speech Research Scientist focusing on singing voice generation, you’ll be working on improving the overall quality and control of ObEN’s virtual singing technology.
 
Responsibilities:

● Develop and improve ObEN’s virtual singing voice technology based on novel voice model with improved glottal source modelingl;

● Explore new approaches for singing voice generation based on deep generative models;

● Develop singing voice generation approach from musical annotation.
 
Requirements:

● PhD with strong experience in speech synthesis, preferably singing voice synthesis demonstrated by publications in top Speech journals and conferences (Icassp, Interspeech, etc);

● Good experience in deep generative models and sequential modelling;

● Strong implementation skills and knowledge in ML;

● Fluent in Python and C++, and good knowledge of deep learning packages;

● Familiarity with linguistic phonetics;

● Knowledge of basic digital signal processing techniques for audio.
 
 
Contact: pierre@oben.com

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SPEECH RESEARCH SCIENTIST (Speech Synthesis)
 
Come join us and build Personal Artificial Intelligence (PAI) -- intelligent 3D avatars that look, sound, and behave like the individual user!
 ObEN is an artificial intelligence company developing a decentralized AI platform for Personal AI (PAI). Founded in 2014, ObEN is a K11, Tencent, Softbank Ventures Korea and HTC Vive X portfolio company.
 
As a Speech Research Scientist focusing on Speech Synthesis, you’ll be working on improving ObEN’s speech synthesis technology. This will include the improvement of our current voice model and the development of new speech generation approaches based on deep generative models.
 
Responsibilities:

● Develop and extend ObEN’s glottal source model, in view of improving the quality, flexibility and control (e.g. voice quality, expressivity) of ObEN’s speech and singing voice synthesis system;

● Develop new speech generation approaches based on deep generative models (e.g. wavenet) with reduced amount of data and better control.
 
Requirements:

● PhD with strong experience in Speech Synthesis demonstrated by publications in top Speech Journals and Conferences (Icassp, Interspeech, etc);

● Expertise in signal processing in particular in the design of voice models (glottal source model, ...) allowing a fine control of the characteristics of the synthesized voice (speech and singing voice);

● Experience in deep generative model of raw audio (wavenet) and Generative Adversarial Network (WGAN);

● Fluent in Python and C++, and good knowledge of deep learning packages (TensorFlow, Theano, Keras, etc);

● Familiarity with linguistic phonetics;

● Knowledge of basic digital signal processing techniques for audio.
 
 
Contact: pierre@oben.com

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SPEECH RESEARCH SCIENTIST (TTS)
 
Come join us and build Personal Artificial Intelligence (PAI) -- intelligent 3D avatars that look, sound, and behave like the individual user!
 ObEN is an artificial intelligence company developing a decentralized AI platform for Personal AI (PAI). Founded in 2014, ObEN is a K11, Tencent, Softbank Ventures Korea and HTC Vive X portfolio company.
 
As a Speech Research Scientist focusing on Text-to-Speech, you will be working on developing cutting-edge deep learning algorithms for voice personalization. This will include the development of structured acoustic models for synthesis allowing the control of factors such as voice timbre, voice quality, language, accent, expressiveness and speaking style and the adaptation/conversion towards a target voice using a reduced amount of data.
 
Responsibilities:
 
● Develop and extend ObEN’s proprietary TTS system, in view of improving the quality and the naturalness of the synthesized voice as well as the similarity to the target voice and reducing the amount of data for speaker adaptation;

● Develop deep generative model of raw speech waveform; ● Develop cross-lingual  approaches (e.g. phonetic posteriorgrams).
 
Requirements:

● PhD with strong research experience in Adaptation of DNN-based TTS systems demonstrated by publications in top Speech journals and conferences (Icassp, Interspeech, etc);

● Strong machine learning background and familiar with standard statistical modeling techniques applied to speech;

● Research experience in deep generative model of raw audio (wavenet) and Generative Adversarial Network (WGAN);

● Fluent in Python and C++, and expert knowledge of deep learning packages (TensorFlow, Theano, Keras, etc);

● Familiarity with linguistic phonetics;

● Knowledge of basic digital signal processing techniques for audio.

 Contact: pierre@oben.com

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Post Doc position (computer science, computational linguistics, physics or similar)
Integrating Models of Vision, Knowledge and Language
 
Statistical models of natural language so far have only considered the preceding words as a context. We would now like to generalize this to include also knowledge of from images or data bases. To this end, suitable neural network architectures will be explored and their properties analysed. Alternative machine learning based approaches will also be considered.
 
Requirements: The successful candidate should have a Master's degree in Computer Science, Computational Linguistics, Physics or a related discipline, with a strong background in mathematics and programming. A good command of English is mandatory as English is the working language of the department. 
 
The position is full time on the German E13 scale and subject to the final approval by the funding agency. Starting dates can be between July and October, 2018. The appointment will be for up to four years. 
 
About the department: The department of Language Science and Technology is one of the leading departments in the speech and language area in Europe.  The flagship project at the moment is the CRC on Information Density and Linguistic Encoding. Furthermore, the department is involved in the cluster of excellence Multimodal Computing and Interaction. It also runs a significant number of European and nationally funded projects. In total it has seven faculty and around 50 postdoctoral researchers and PhD students.
 
How to apply:  Please send us  a letter of motivation,  your CV,  your transcripts,  a list of publications,  and the names and contact information of at least two references, as a single PDF or a link to a PDF if the file size is more than 3 MB.
 
Please apply by April 10th, 2018.
 
Contact: If you are interested in the project, please send an email to Dietrich Klakow (dietrich.klakow@lsv.uni-saarland.de)

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PhD Position in Experimental Mechanics of Materials/Structures
“From the vocal-fold 3D structure and micro-mechanics to the design of biomimetic materials”
 
Location : 3SR Lab, CoMHet team, Grenoble, France lucie.bailly@3sr-grenoble.fr, laurent.orgeas@3sr-grenoble.fr, sabine.rollandduroscoat@3sr-grenoble.fr
 
Collaboration : GIPSA-lab, VSLD team, Grenoble, France Nathalie.Henrich@gipsa-lab.fr
 
Project summary
The vocal folds are soft multi-layered laryngeal tissues, owning remarkable vibro-mechanical performances. Composed of collagen and elastin microfibrils’ networks, the upper layers play a major role in the vocal-fold vibrations. However, the impact of these tissues’ histological features on their mechanical behavior is still poorly known. This is mainly ascribed to their challenging experimental characterization at the scale of their fibrous networks. 
 
Therefore, this PhD project aims to gain an in-depth understanding of the link between the micromechanics of vocal-fold tissues and their unique vibratory macroscale performances. The strategy will be : 1. To go further in the investigation of the vocal-fold 3D architecture and micromechanics and behaviour upon finite deformation. This step will be based on experimental biomechanical campaigns and unprecedented synchrotron X-ray in situ microtomography ; 2. To use these data to mimic and process fibrous biomaterials  with tailored structural and biomechanical properties ; 3. To characterize the vibro-mechanical properties of these biomaterials at different scales (macro/micro) and frequencies (low/high). 
Location and practical aspects
The successful applicant will be hosted by the laboratory Soils, Solids, Structures, Risks (3SR, UMR5521 - Grenoble, France - www.3sr-grenoble.fr/) in the “CoMHet” team. A part of his/her work will also be conducted in the Images, Speech, Signal and Automation Laboratory (GIPSA-lab, UMR5216 - Grenoble, France - www.gipsalab.grenoble-inp.fr/). This project will benefit from a collaboration existing between researchers in mechanical engineering, voice production and clinicians from Grenoble University Hospital (LADAF).
The PhD fellowship offer is available from September 2018 (possible adjustments of this starting date if need be) for a period of 3 years (financial support acquired from ANR MicroVoice project). 
Applications Candidates with academic backgrounds in solid mechanics, materials science and engineering are expected. Specific skills in dynamics of composites, vibromechanics, and experimental mechanics will be appreciated. Additional knowledge in acoustics and/or biomechanics of soft tissues will be interestingly examined. 
Interested candidates should send their CV, a cover letter and official transcripts of the last two years before 2018, April the 30th to Lucie BAILLY, lucie.bailly@3sr-grenoble.fr, (+33) (0)4 76 82 70 85.

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Nous recherchons un-e stagiaire dans le cadre d'un projet ayant pour but l'actualisation
d?un inventaire de ressources linguistiques pour les langues régionales françaises, ainsi
que la négociation des droits pour permettre leur partage avec la communauté des
technologies de la langue.

Les tâches consisteront principalement en:

?    La mise à jour de l?inventaire de ressources linguistiques existant
?    L'étude technique et juridique des conditions de partage actuelles de ces ressources
(analyse des formats d?exploitation des ressources et identification des droits
d?utilisation en coopération avec un expert juridique en interne)
?    La négociation avec les fournisseurs, la définition des conditions de réutilisation
des ressources linguistiques, l?établissement de contrats de distribution,
?    La description et l?intégration des ressources disponibles dans le catalogue ELRA
?    La rédaction d?un rapport final

Profil:
?    Niveau master 2 traitement automatiques des langues ou domaines assimilés
?    Durée : 6 mois
?    Aptitude à travailler tant de façon indépendante qu?au sein d?une équipe
?    Forte aptitude rédactionnelle et analytique
?    Convention de stage requise

Toute candidature sera étudiée jusqu?à ce que le poste soit pourvu. Le poste est basé à
Paris.

Salaire : en fonction des qualifications et expériences.

Les candidatures doivent être adressées par courriel (lettre de motivation et curriculum
vitae) à:
ELDA
9, rue des Cordelières
75013 Paris
FRANCE
Email : job@elda.org

ELDA, unité opérationnelle de l?association ELRA, est chargée de promouvoir le
développement de ressources linguistiques sous toutes les formes électroniques
utilisables, en particulier sous la forme de corpus oraux et écrits, de lexiques et de
bases terminologiques. Depuis sa création en 1995, ELDA s?est affirmée comme un centre
unique en Europe pour la distribution de ressources linguistiques, capable de répondre
aux divers besoins des développeurs de technologie. Ses activités se développent
maintenant vers de nouveaux types de ressources linguistiques (données de type
multimodal/multimédia). Certaines ressources linguistiques sont conçues au cours de
projets (co-)financés par ELDA. Celles-ci sont ensuite compilées sous la forme d?un
catalogue de ressources linguistiques. ELDA est impliquée dans un certain nombre de
projets européens et nationaux. ELDA s?intéresse également aux problèmes juridiques en
rapport avec les ressources linguistiques, réalise régulièrement des études de marché sur
les besoins des utilisateurs, et travaille à l?amélioration des procédures de validation
des ressources.

Pour de plus amples renseignements concernant ELRA/ELDA, voir : http://www.elra.info ou
www.elda.org

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Telecom ParisTech has one new permanent (indefinite tenure) faculty position (Associate Professor) in machine learning. Applicants from machine learning for speech processing, natural language processing or affective computing are welcomed.

More information on the social computing topic is avalable here : https://www.tsi.telecom-paristech.fr/en/research/1885-2/social-computing-topic/ 

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

Faculty position (Associate professor) at Telecom ParisTech in

Machine-Learning.

Important Dates

?    May 25th, 2018: closing date

?    Mid June: hearings of preselected candidates

Telecom ParisTech?s [1] machine learning, statistics and signal processing group (a.k.a S²A group) [2], within the laboratoire de traitement et communication de l?information (LTCI) [5], is inviting applications for a permanent (indefinite tenure) faculty position at the *Associate Professor* level (Maitre de Conferences) in *Machine learning*.

Main missions

The recruit will be expected to:

Research activities

?    Develop groundbreaking research in the field of theoretical or applied machine learning,   targeting applications that are well aligned with the topics of the S²A group [3] and the Images, Data & Signals department [4], which include (and is not restricted to) time series analysis (audio, ?), reinforcement learning, natural language processing, social signal processing, predictive maintenance, biomedical or physiological signal analysis, recommendation, finance, health, ?. 

?    Develop both academic and industrial collaborations on the same topic, including collaborative activities with other Telecom ParisTech research departments and teams, and research contracts with industrial players

?    Set up research grants and take part in national and international collaborative research projects

Teaching activities

?    Participate in teaching activities at Telecom ParisTech and its partner academic institutions (as part of joint Master programs), especially in machine learning and Data science, 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, applied mathematics, signal processing,

?    Experience in teaching

?    Good command of English

The ideal candidate will also (optionally) have:

?    Experience in temporal data analysis problems (sequence prediction, multivariate time series, probabilistic graphical models, recurrent neural networks...)

NOTE:

The candidate does *not* need to speak French to apply, just to be willing to learn the language (teaching will be mostly given in English)

Other skills expected include:

?    Capacity to work in a team and develop good relationships with colleagues 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, check [6] (in French)

 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)

Contacts :

Slim Essid (Coordinator of the ADASP team)

Florence d?Alché-Buc (Professor, Machine Learning)

Stéphan Clémençon (Head of the S²A group)

Gaël Richard (Head of the IDS department)

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

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

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

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The Social Cognitive Systems group (headed by Prof. Dr. Stefan Kopp; Cluster of Excellence Cognitive Interaction Technology, Bielefeld University, Germany) is currently looking for a PhD-student in a research project investigating strategies for human?robot-interaction, with a focus on generation of multimodal spoken dialogue behaviour.

Applicants should have a masters degree in computer science or (computational) linguistics with a focus on machine learning, statistical methods in natural language processing, and/or dialogue modelling and should have strong communication skills and be motivated to work in an interdisciplinary team of computer scientists, psychologists, engineers, and designers.

The position is fully paid (TV-L 13) with funding for three years. The official job advertisement (in German) can be found here: https://scs.techfak.uni-bielefeld.de/scswp/wordpress/wp-content/uploads/2018/03/wiss18072.pdf The deadline for applications to receive full consideration is 2018-04-06.

If you have any questions or want to know more about the research project, our research group, or living and working in Bielefeld, don't hesitate to contact Stefan Kopp <skopp@techfak.uni-bielefeld.de>.

--

Hendrik Buschmeier

Social Cognitive Systems Group, CITEC, Bielefeld University

https://purl.org/net/hbuschme

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RESEARCH LINGUIST
 
Come join us and build Personal Artificial Intelligence (PAI) -- intelligent 3D avatars that look, sound, and behave like the individual user!
 ObEN is an artificial intelligence company developing a decentralized AI platform for Personal AI (PAI). Founded in 2014, ObEN is a K11, Tencent, Softbank Ventures Korea and HTC Vive X portfolio company.
 
As a Research Linguist, you will collaborate with other scientists who are experts in speech engineering, natural language processing, and computer vision. You will be working on a variety of tasks to improve technologies for speech synthesis, speech recognition, visual speech, and natural language processing. 
 
The tasks include: ● Design material and procedures to collect spoken and written language data; ● Design schemas and label/tag sets to annotate recordings and text with phonetic, prosodic, semantic, and syntactic features; ● Design methods and protocols to ensure the quality of linguistic data and annotations; ● Design perceptual or linguistic tests to evaluate the performance of speech and language systems; ● Contribute to the formalization of speech and language models by offering linguistic knowledge, identifying issues and providing solutions. 
 
Basic qualifications: ● Masters or higher degree in Linguistics or a closely-related field ● Specialization in Phonetics or Phonology ● Native or near-native proficiency in Japanese or Korean ● Ability to use programming scripts
 
Preferred qualifications: ● Knowledge of scripting languages, e.g., Python ● Background in Psychology/Psycholinguistics ● Willingness to accept reprioritization as necessary
 
 
Contact: pierre@oben.com

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SPEECH RESEARCH SCIENTIST (ASR)
 
Come join us and build Personal Artificial Intelligence (PAI) -- intelligent 3D avatars that look, sound, and behave like the individual user!
 ObEN is an artificial intelligence company developing a decentralized AI platform for Personal AI (PAI). Founded in 2014, ObEN is a K11, Tencent, Softbank Ventures Korea and HTC Vive X portfolio company.
 
As an ASR Research Scientist, you’ll be working on developing tools to automate speech data               acquisition and selection from diverse sources of data for the training of ObEN’s speech              technology components.
 
Responsibilities:
 
● Develop and extend ObEN’s proprietary ASR systems for different languages (English, Chinese, Korean, Japanese), in view of improving the robustness against environmental and channel distortion; ● Develop long (>1h) speech-text alignment systems; ● Develop lyrics-singing voice alignment systems; ● Develop tools and measures for data selection (confidence scores, acoustic measures); ● Develop tools for metadata extraction from speech and text (e.g: emotion, speakerID, etc).
 
Requirements: ● PhD with strong research experience in ASR demonstrated by publications in top Speech Journals and Conferences (ICASSP, Interspeech, ASRU, etc.); ● Experience with robust ASR,  long speech-text alignment, lightly supervised approaches and confidence measures computation; ● Fluent in Python and C++, excellent knowledge of Kaldi; ● Strong machine learning background and familiar with standard statistical modeling techniques applied to speech; ● Good knowledge of deep learning packages (Tensorflow, Theano, Keras, etc).
 
 
Contact: pierre@oben.com

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SPEECH RESEARCH SCIENTIST (Prosody Modeling)
 
Come join us and build Personal Artificial Intelligence (PAI) -- intelligent 3D avatars that look, sound, and behave like the individual user!
 ObEN is an artificial intelligence company developing a decentralized AI platform for Personal AI (PAI). Founded in 2014, ObEN is a K11, Tencent, Softbank Ventures Korea and HTC Vive X portfolio company.
 
As a Speech Research Scientist focusing on Prosody Modeling, you will be working on developing new prosody models for different languages (Chinese, English, Japanese, Korean) to improve the naturalness and the similarity of the synthesized voice and to allow a better control of its expressivity. 
 
Responsibilities: ● Develop new prosody model for different languages, adaptable using a small amount of data; ● Develop generic prosodic models for different expressivity which can be applied to any voice; ● Develop sentiment analysis algorithms to control expressivity from text input.   Requirements: ● PhD with strong experience in Prosody Modeling for Speech Synthesis demonstrated by publications in top Speech Journals and Conferences (Speech prosody, Icassp, Interspeech, etc); ● Strong implementation skills and general knowledge in ML; ● Fluent in Python and C++, and good knowledge of deep learning packages; ● Familiarity with linguistic phonetics; ● Knowledge of basic digital signal processing techniques for audio.
 
 
Contact: pierre@oben.com

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SPEECH RESEARCH SCIENTIST (Singing Voice Synthesis)
 
Come join us and build Personal Artificial Intelligence (PAI) -- intelligent 3D avatars that look, sound, and behave like the individual user!
 ObEN is an artificial intelligence company developing a decentralized AI platform for Personal AI (PAI). Founded in 2014, ObEN is a K11, Tencent, Softbank Ventures Korea and HTC Vive X portfolio company.
 
As a Speech Research Scientist focusing on singing voice generation, you’ll be working on improving the overall quality and control of ObEN’s virtual singing technology.
 
Responsibilities: ● Develop and improve ObEN’s virtual singing voice technology based on novel voice model with improved glottal source modelingl; ● Explore new approaches for singing voice generation based on deep generative models; ● Develop singing voice generation approach from musical annotation.
 
Requirements: ● PhD with strong experience in speech synthesis, preferably singing voice synthesis demonstrated by publications in top Speech journals and conferences (Icassp, Interspeech, etc); ● Good experience in deep generative models and sequential modelling; ● Strong implementation skills and knowledge in ML; ● Fluent in Python and C++, and good knowledge of deep learning packages; ● Familiarity with linguistic phonetics; ● Knowledge of basic digital signal processing techniques for audio.
 
 
Contact: pierre@oben.com 
 

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SPEECH RESEARCH SCIENTIST (Speech Synthesis)
 
Come join us and build Personal Artificial Intelligence (PAI) -- intelligent 3D avatars that look, sound, and behave like the individual user!
 ObEN is an artificial intelligence company developing a decentralized AI platform for Personal AI (PAI). Founded in 2014, ObEN is a K11, Tencent, Softbank Ventures Korea and HTC Vive X portfolio company.
 
As a Speech Research Scientist focusing on Speech Synthesis, you’ll be working on improving ObEN’s speech synthesis technology. This will include the improvement of our current voice model and the development of new speech generation approaches based on deep generative models.
 
Responsibilities: ● Develop and extend ObEN’s glottal source model, in view of improving the quality, flexibility and control (e.g. voice quality, expressivity) of ObEN’s speech and singing voice synthesis system; ● Develop new speech generation approaches based on deep generative models (e.g. wavenet) with reduced amount of data and better control.
 
Requirements: ● PhD with strong experience in Speech Synthesis demonstrated by publications in top Speech Journals and Conferences (Icassp, Interspeech, etc); ● Expertise in signal processing in particular in the design of voice models (glottal source model, ...) allowing a fine control of the characteristics of the synthesized voice (speech and singing voice); ● Experience in deep generative model of raw audio (wavenet) and Generative Adversarial Network (WGAN); ● Fluent in Python and C++, and good knowledge of deep learning packages (TensorFlow, Theano, Keras, etc); ● Familiarity with linguistic phonetics; ● Knowledge of basic digital signal processing techniques for audio.
 
 
Contact: pierre@oben.com

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SPEECH RESEARCH SCIENTIST (TTS)
 
Come join us and build Personal Artificial Intelligence (PAI) -- intelligent 3D avatars that look, sound, and behave like the individual user!
 ObEN is an artificial intelligence company developing a decentralized AI platform for Personal AI (PAI). Founded in 2014, ObEN is a K11, Tencent, Softbank Ventures Korea and HTC Vive X portfolio company.
 
As a Speech Research Scientist focusing on Text-to-Speech, you will be working on developing cutting-edge deep learning algorithms for voice personalization. This will include the development of structured acoustic models for synthesis allowing the control of factors such as voice timbre, voice quality, language, accent, expressiveness and speaking style and the adaptation/conversion towards a target voice using a reduced amount of data.
 
Responsibilities:
 
● Develop and extend ObEN’s proprietary TTS system, in view of improving the quality and the naturalness of the synthesized voice as well as the similarity to the target voice and reducing the amount of data for speaker adaptation; ● Develop deep generative model of raw speech waveform; ● Develop cross-lingual  approaches (e.g. phonetic posteriorgrams).
 
Requirements: ● PhD with strong research experience in Adaptation of DNN-based TTS systems demonstrated by publications in top Speech journals and conferences (Icassp, Interspeech, etc); ● Strong machine learning background and familiar with standard statistical modeling techniques applied to speech; ● Research experience in deep generative model of raw audio (wavenet) and Generative Adversarial Network (WGAN); ● Fluent in Python and C++, and expert knowledge of deep learning packages (TensorFlow, Theano, Keras, etc); ● Familiarity with linguistic phonetics; ● Knowledge of basic digital signal processing techniques for audio.
 Contact: pierre@oben.com

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Des postes d'ATER en Traitement automatique des langues et de la Parole sont disponibles à la faculté des lettres de Sorbonne Université. Le lien pour postuler est http://concours.univ-paris4.fr/PostesAter?entiteBean=posteCandidatureCourant

Les conditions pour candidater sont disponibles sur http://lettres.sorbonne-universite.fr/ater.

Cordialement,

Claude Montacié
claude.montacie@sorbonne-universite.fr

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Dear colleagues,
Please find attached the description of a three-years doctoral position at the University Sorbonne Nouvelle to be filled at the last term of 2018.

The Laboratory of Phonetics and Phonology (http://lpp.in2p3.fr/), Paris, France, offers a funded position for a PhD candidate for a period of three years on the acoustic phonetic markers of inter and intra-speaker variability with a special notice considering the normalization of procedures.

We would be most grateful if you could also distribute this information among other persons who may be interested by this offer.

Cédric Gendrot et Cécile Fougeron

Descriptif de l?offre :

Offre de contrat doctoral par le Laboratoire de Phonétique et Phonologie : « Marqueurs phonétiques et acoustiques de la variabilité inter- et intra-individuelle »      

Le Laboratoire de Phonétique et Phonologie propose un contrat doctoral de 3 ans financé par l?ANR pour la rentrée universitaire 2018.

Le thème du doctorat proposé ici a pour objectif d'analyser les marqueurs phonétiques et acoustiques de la variabilité inter et intra locuteurs. Une attention particulière sera portée à la standardisation des méthodes d?analyse proposées, permettant leur transposition dans des domaines d?application connexes, dont celui du traitement automatique de la parole.

Il s?agira de prendre en compte des caractéristiques de la voix/parole très liées au contexte de la comparaison de voix. Dans la mesure où les variations de la parole sont multifactorielles, il apparaît indispensable d?établir des standards de mesures objectives pour lesquelles les méthodologies récentes de la phonétique expérimentale peuvent apporter une garantie.

On s?intéressera notamment aux marqueurs acoustiques qui retranscrivent des propriétés physiologiques individuelles ainsi qu?aux habitudes articulatoires, vecteurs d?identité sociale.

Le/la doctorant(e) effectuera ses recherches au LPP (Laboratoire de Phonétique et de Phonologie), une unité de recherche mixte CNRS/Université Paris3 Sorbonne Paris Cité. Voir les travaux sur ce thème du Laboratoire de Phonétique et de Phonologie http://lpp.in2p3.fr

Le/la candidat(e) sélectionné(e) sera encadré(e) par Cédric Gendrot et Cécile Fougeron, respectivement enseignant-chercheur de l?Université Sorbonne Nouvelle et Directrice de recherche au CNRS. Il/elle dépendra de l'Ecole Doctorale ED268 de l'Université Sorbonne nouvelle.

Le/la doctorant(e) bénéficiera des ressources du laboratoire, de l'Ecole Doctorale ED268  et de l'environnement de recherche interdisciplinaire du Laboratoire d'Excellence EFL. Il/elle pourra assister à des séminaires hebdomadaires de recherche phonétique et phonologie au LPP et d'autres équipes de recherche, suivre des conférences données par des professeurs invités de stature internationale, des formations, des colloques et des écoles d'été.

? Conditions

 - avoir une bonne maitrise de la langue française.

- avoir mené avec succès un premier projet de recherche personnel

- aucune condition de nationalité n'est exigée.

- avoir de très bonnes connaissances en traitement de données de type phonétique acoustique.

- des connaissances en informatique et en analyse statistique seraient un plus. 

? Pièces à joindre pour la candidature

1.         un CV

2.         une lettre de motivation

3.         le mémoire de master 2 en phonétique

4.         le nom de deux référents (avec leur adresse courriel)

Date limite de candidature: 30 juin 2018

Les dossiers complets seront à envoyer par mail au plus tard le 30 juin 2018 à Cédric Gendrot (cgendrot@univ-paris3.fr) et Cécile Fougeron (cecile.fougeron@univ-paris3.fr)

• Présélection sur dossier et Audition des candidats présélectionnés

Les candidats présélectionnés seront auditionnés entre le 2 et le 6 juillet 2018) sur place ou par visio-conférence.  

Contact pour plus d?information : 

Cédric Gendrot : cgendrot@univ-paris3.fr

Cécile Fougeron : cecile.fougeron@univ-paris3.fr

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