| 6-1 | (2016-12-02) Tenure senior research position at INRIA Bordeaux France
Flowers Lab at Inria (Bordeaux, France)
Deadline: 16th december
We are searching highly qualilified candidates for a tenure senior research position (full time research, no teaching mandatory).
Candidates should have an outstanding academic track record in one or two of the following domains:
1) Computational modelling of cognitive development, including the following research topics and methods:
- Models of exploration and active learning in humans and animals
- Models of human reinforcement learning and decision making
- Bayesian or neuronal models of development
- Models of autonomous lifelong learning
- Models of tool learning
- Sensorimotor, language and social development
- Strong experience of collaborations with developmental psychologists or neuroscientists
2) Lifelong autonomous machine learning and artificial intelligence, including:
- Unsupervised deep reinforcement learning
- Intrinsic motivation
- Developmental learning, curriculum learning
- Contextual bandit algorithms
- Multitask and transfer learning
- Hierarchical learning
- Strong experience in benchmarking with robotic or virtual world setups
As the Flowers lab domains of application are robotics/HRI/HCI and educational technologies, experience in one of these two
domains would be a clear asset.
Experience in writing successful grant proposals will also be considered positively.
Candidates should have a strong postdoc experience after their PhD, or may already be at the level of occupying a research position
in a university or research organization.
The Flowers Lab: developmental robotics and lifelong multitask machine learning
===================================================================
The Flowers Lab, headed by Pierre-Yves Oudeyer, gathers a team of ~20 members and has been one of the pioneers of developmental robotics and lifelong machine learning
and artificial intelligence in the last decade, in particular through developping models of intrinsically motivated learning of repertoires of skills that have both contributed
to advance understanding of human curiosity and development, and to advance incremental online multitask machine learning techniques in difficult high-dimensional
robotic spaces.
This work in the Flowers lab are conducted in the context of large international projects (e.g. ERC grant, European projects 3rdHand and DREAM, HFSP project Neurocuriosity),
with interdisicplinary collaborations with other labs in neuroscience, psychology, machine learning and robotics. The successful candidates would be directly
involved in these international collaborations.
The Flowers Lab has is also developping applications of these concepts and techniques in the domain of educational technologies, including adaptive
intelligent tutoring systems (using bandit algorithms), educational robotics, and software that stimulate curiosity and learning in humans.
The Flowers lab has recently spin-off the Pollen Robotics startup company, and is involved in multiple collaborations with industrials through Inria's strong
support towards impacting both science and industry.
Inria and EnstaParistech
===================
The lab is within Inria, which is a prestigious, and also the largest, public European research insitution focused on computer science, mathematics and their applications.
Inria's teams and researchers (> 2800 employees) have received prestigious awards, coordinate many international projects, and have created strong innovations now used in many
parts of industry. Inria research center in Bordeaux gathers around 300 researchers.
The Flowers Lab is also associated to EnstaParisTech, which is a prestigious French engineering school (university).
Bordeaux
========
The Flowers lab in Bordeaux is located in a great building on the border of one of the world most famous vineyard, and 10mn by tram from Bordeaux town center
Web
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How to apply
===========
Then, a pre-selection will be made and a full application with a detailed research statement and program will have to be submitted early february.
The successful candidate would begin to work between september and december 2017.
Pierre-Yves Oudeyer
Research director, Inria
Head of Flowers Lab
Inria and Ensta ParisTech
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| 6-2 | (2016-12-19) Postdoc at LIMSI, Orsay, France
LIMSI offers a one-year postdoctoral position on unsupervised identification of characters in TV series.
--- Keywords ---
Deep learning, speech processing, natural language processing, computer vision
--- Project summary ---
Automatic character identification in multimedia videos is an extensive and challenging problem. Person identification serves as foundation and building block for many higher level video analysis tasks, for example semantic indexing, search and retrieval, interaction analysis and video summarization.
The goal of this project is to exploit textual, audio and video information to automatically identify characters in TV series and movies without requiring any manual annotation for training character models. A fully automatic and unsupervised approach is especially appealing when considering the huge amount and growth of available multimedia data. Text, audio and video provide complementary cues to the identity of a person, and thus allow to better identify a person than from either modality alone.
To this end, we will address three main research questions: unsupervised clustering of speech turns (i.e. speaker diarization) and face tracks in order to group similar tracks of the same person without prior labels or models; unsupervised identification by propagation of automatically generated weak labels from various sources of information (such as subtitles and speech transcripts); and multimodal fusion of acoustic, visual and textual cues at various levels of the identification pipeline.
While there exist many generic approaches to unsupervised clustering , they are not adapted to heterogeneous audiovisual data (face tracks vs. speech turns) and do not perform as well on challenging TV series and movies content as they do on other controlled data. Our general approach is therefore to first overcluster the data and make sure that clusters remain pure , before assigning names to these clusters in a second step. On top of domain specific improvements for either modality alone, we expect joint multimodal clustering to take advantage of three modalities and improve clustering performance over each modality alone.
Then, unsupervised identification aims at assigning character names to clusters in a completely automatic manner (i.e. using only available information already present in the speech and video ). In TV series and movies, character names are usually introduced and reiterated throughout the video. We will detect and use addresser/addressee relationships in both speech transcripts (using named entity detection techniques) and video (using mouth movements, viewing direction and focus of attention of faces). This allows to assign names to some clusters, learn discriminative models and assign names to the remaining clusters.
For evaluation, we will extend and further annotate a corpus of four TV series (57 episodes) and one movie series (8 movies), a total of about 50 hours of video. This diverse data covers different filming styles, type of stories and challenges contained in both video and audio. We will evaluate the different steps of this project on this corpus, and also make our annotations publicly available for other researchers working in the field.
---
--- Information ---
PhD in machine learning (experience in natural language processing, computer vision and/or speech processing is appreciated)
Location: LIMSI - CNRS, Orsay, France
Duration: 12 months, starting date to be defined with the selected candidate
Contact: Hervé Bredin (bredin@limsi.fr)
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| 6-3 | (2017-01-12) Internship INA Paris: Segmentation Parole/Musique de documents multimédias à l’aide de réseaux de neurones profonds
Segmentation Parole/Musique de documents multimédias à
l’aide de réseaux de neurones profonds
Stage de fin d’études d’Ingénieur ou de Master 2 – 2016-2017
Mots clés: Deep Learning, Segmentation Audio, Machine Learning, Music Information
Retrieval, Open Data
Contexte
Les missions de l’institut national de l’audiovisuel (Ina) consistent à archiver et à valoriser la
mémoire audio-visuelle française (radio, télévision et médias Web). A ce jour, plus de 15 millions
d’heures de documents télé et radio sont conservés, dont 1,5 millions d’heures numérisées. En
raison de la masse de données considérée, il n’est techniquement pas possible de procéder à une
description manuelle, systématique et détaillée de l’ensemble des archives. Il est donc nécessaire
d’utiliser des techniques d’analyse automatique du contenu pour optimiser l’exploitation de cette
masse de données.
Objectifs du stage
La segmentation Parole/Musique (SPM) consiste à segmenter un flux audio en zones homogènes de
parole et de musique. Cette étape est nécessaire en amont de tâches d’indexation haut niveau, telles
que la reconnaissance de la parole, du locuteur, du morceau ou du genre musical. Pour ces
différentes raisons, cette tâche a suscité beaucoup d’intérêts au sein des communautés de traitement
de la parole, ainsi qu’en indexation musicale.
L’utilisation de systèmes de SPM à l’Ina répond à trois cas d’usage principaux. En premier lieu, il
s’agit de localiser rapidement les zones d’intérêt au sein des médias, pour fluidifier les processus de
description des archives, réalisés manuellement par des documentalistes. La description manuelle
des archives est coûteuse, et réalisée avec un niveau de détail variable: les journaux télévisés étant
décrits plus finement que les fonds radio anciens. Les systèmes SPM peuvent ainsi permettre de
faciliter la navigation dans des fonds d’archives sous-documentés. Le dernier cas d’usage
correspond à la segmentation en morceaux de musique: consistant à détecter le début et la fin des
morceaux. Cette tâche permet de mesurer la durée des extraits musicaux présents dans les archives,
et ainsi rémunérer les sociétés d’auteurs concernées lorsque les archives sont commercialisées.
A ce jour, un certain nombre de situations restent difficiles pour les systèmes SMS. Il s’agit
notamment la différentiation entre voix parlée et voix chantée, notament dans certains styles
musicaux où les propriétés spectrales de la voix chantée et parlée sont similaires. Une autre
difficulté rencontrée est liée aux cas où la parole est superposée à la musique, ce qui arrive assez
fréquemment dans les émissions radio et télé. Une autre difficulté rencontrée par les systèmes
actuels est la liée à la finesse de la segmentation temporelle, généralement de l’ordre de la seconde.
L’objectif du stage consiste à concevoir des systèmes basés sur l’utilisation de réseaux de neurones
profonds pour la segmentation parole/musique d’archives audio-visuelles. Les méthodes proposées
devront prendre en charge la diversité des archives de l’Ina (archives radio des années 1930 à nos
jours). Une partie du stage sera consacrée à l’analyse des corpus existants, et à la constitution d’un
corpus annoté (interprète, morceau, genre, locuteur, ...) permettant d’avoir un maximum de contrôle
sur l’ensemble des paramètres testés lors des évaluations. L’autre partie du stage sera consacré à la
mise au point d’architectures basées sur des réseaux de neurones profonds pour la SPM, qui sera
réalisée dans la continuité des travaux en cours utilisant des réseaux de neurones convolutionnels.
Le langage de programmation utilisé dans le cadre de ce stage sera Python. Le stagiaire aura accès
aux ressources de calcul de l’Ina (cluster et serveurs GPU).
Conditions du stage
Le stage se déroulera sur une période de 6 mois, au sein de l’équipe recherche de l’Ina. Il aura lieu
sur le site Bry2, situé au 18 Avenue des frères Lumière, 94366 Bry-sur-Marne. Le stagiaire sera
encadré par David Doukhan (ddoukhan@ina.fr) et Jean Carrive (jcarrive@ina.fr), et percevra une
rémunération mensuelle de 527,75 euros/mois.
Bibliographie
Jimena, R. L., Hennequin, R., & Moussallam, M. (2015). Detection and characterization of singing
voice using deep neural networks.
Peeters, G. (2007). A generic system for audio indexing: Application to speech/music segmentation
and music genre recognition. In Proc. DAFX (Vol. 7, pp. 205-212).
Pinto, N., Doukhan, D., DiCarlo, J. J., & Cox, D. D. (2009). A high-throughput screening approach
to discovering good forms of biologically inspired visual representation. PLoS Comput Biol, 5(11),
e1000579.
LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436-444.
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| 6-4 | (2017-01-15) Postdoctoral Positions in Linguistics/Sciences du Langage, LPL, CNRS, Aix-Marseille, France
Call for Postdoctoral Positions in Linguistics/Sciences du Langage
Institution: Laboratoire Parole et Langage (CNRS, Aix-Marseille Université)
Location: Aix-en-Provence, France
No. of positions: 2
Duration: 18-24 months
Application deadline: 1 March 2017
The Laboratoire Parole et Langage (CNRS, Aix-Marseille Université) invites applications for two postdoctoral positions to be supported by a grant from the A*MIDEX Foundation. The funded project explores the relationship between social variables and linguistic representation, and seeks to develop and extend an explicit cognitive model that accounts for the effects of socio-indexical cues on production and perception. The empirical basis for the project involves a combination of experimentation (production, perception, ERP), corpus analysis, and computational modeling. The selected applicants will engage with an interdisciplinary team from the Institute of Language, Communication, and the Brain which includes experts in neuroscience, psychology, computer science, and mathematics, among other areas.
A special emphasis of the project concerns issues in prosody and intonation, so an interest in, or experience with, prosody is highly desirable. In addition, the ideal applicant will have experience in one or more of the following areas:
Sociolinguistics (quantitative)
Machine learning and statistical modeling (esp. sound structure/phonetics)
Design and analysis of speech corpora
Prosody and meaning (esp. information structure)
Knowledge of French is not essential. Each postdoctoral appointment is for approximately 18-24 months depending on the starting date. Candidates must have completed all PhD requirements before the starting date. The starting date is flexible, though the position should be filled by 1 June 2017.
Applications should include (i) a cover letter that relates the applicants’ experience and interests to the project, (ii) a comprehensive CV, (iii) a PDF copy of all publications or a list of links where these can be accessed, and (iv) the names and contact information of at least two references.
Applications in French or English may be sent by email to Oriana Reid-Collins at oriana.reid-collins@lpl-aix.fr.
For further inquiries regarding the position or the project, please contact James Sneed German (principal investigator) at james.german@lpl-aix.fr.
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| 6-5 | (2017-01-20) Postdoc in Mental Health, Affective Computing and Machine Learning at CMU, Pittsburgh, PA, USA
Postdoc in Mental Health, Affective Computing and Machine Learning
Carnegie Mellon University, School of Computer Science
University of Pittsburg, School of Medicine
*** US citizenship or a green card is required to be eligible for consideration. ***
The Multimodal Communication and Machine Learning Laboratory (MultiComp Lab) at Carnegie Mellon University is seeking creative and energetic applicants for a two-year postdoctoral position. This opportunity is part of NIMH-funded training program based at the University of Pittsburg School of Medicine. The position includes a competitive salary with full benefits and travel resources.
Using recent progress in machine learning and artificial intelligence, the postdoc will study patient’s multimodal behaviors (verbal, visual and vocal) during semi-structured clinical interviews to identify behavior markers of mental health disorders (e.g., depression, schizophrenia, suicidal ideation). The postdoc will work under the supervision of Dr. Louis-Philippe Morency (CMU MultiComp Lab’s director), in collaboration with clinicians and researchers at University of Pittsburgh’s Western Psychiatric Institute and Clinic.
The successful applicant will have an extensive research experience in automatic multimodal behavior analysis in the mental health domain, including facial and gesture analysis, acoustic signal processing, linguistic computation and multimodal machine learning.
Required
- PhD in computer science or mental-health related field (at the time of hire)
- Research experience in human behavior analysis, affective computing and machine learning
- US citizenship or a green card is required to be eligible for consideration
Desired
- Publications in top machine learning, speech processing and/or computer vision conferences and journals.
- Research involving clinical patients with mental health disorders (e.g., depression, schizophrenia, suicidal ideation)
- Experience mentoring graduate and undergraduate students
Job details
- Preferred start date: May 1st, 2017 (negotiable)
- Candidate will work under the supervision of Dr. Louis-Philippe Morency, MultiComp Lab’s director, at CMU Pittsburgh campus.
- Research will be performed in collaboration with clinicians and researchers at University of Pittsburgh’s Western Psychiatric Institute and Clinic.
- Competitive salary with full benefits and travel resources.
How to apply
- Email applications should be sent to morency@cs.cmu.edu with the title “Postdoc application – NIMH program”
- A single PDF file titled FirstNameLastName.pdfshould be attached to the email, including:
- a brief cover letter (with expected date of availability),
- a CV including list of publications and email addresses of 3 references,
- two representative publications (including full citation information)
=====================
Louis-Philippe Morency
Assistant Professor
School of Computer Science
Carnegie Mellon University
Multimodal Commination and Machine Learning Laboratory
https://www.cs.cmu.edu/~morency/
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| 6-6 | (2017-01-21) Internship at INRIA Bordeaux, France
Stage de 6 mois pour étudiants en Master2 à INRIA Bordeaux
Titre du Sujet de Stage :Analyse de la parole pour le diagnostic différentiel entre maladie de Parkinson et l'atrophie multisystématisée
Description :
La maladie de Parkinson (MP) et l'atrophie multisystématisée (AMS) sont des maladies neurodégénératives. La dernière appartient au groupe des troubles parkinsoniens atypiques et est responsable d?un pronostic péjoratif. Dans les premiers stades de la maladie, les symptômes de MP et AMS sont très similaires, surtout pour AMS-P où le syndrome parkinsonien prédomine. Le diagnostic différentiel entre AMP-P et MP peut être très difficile dans les stades précoces de la maladie, tandis que la certitude de diagnostic précoce est important pour le patient en raison du pronostic divergent. En effet, malgré des efforts récents, aucun marqueur objectif valide n'est actuellement disponible pour guider le clinicien dans ce diagnostic différentiel. La nécessité de ces marqueurs est donc très élevé dans la communauté de la neurologie, en particulier compte tenu de la gravité du pronostic de AMS-P.
Les troubles de la parole, communément appelés dysarthrie, sont un symptôme précoce commun aux deux maladies et d'origine différente. Notre approche consiste à utiliser la dysarthrie, grâce à un traitement numérique des enregistrements vocaux des patients, comme un vecteur pour distinguer entre MP et AMS-P dans les stades précoces de la maladie.
L'objectif du stage est d'utiliser des techniques connues de mesure de perturbation de la voix ainsi que des techniques récemment développées par l'équipe GeoStat d'Inria pour faire une étude expérimentale préliminaire sur le pouvoir discriminant de ces différentes mesures. Cette études se fera sur des bases de données médicales existantes.
Le stage déboucherait sur une bourse de thèse de doctorat dans le cadre d'une allocation ANR qui finance ce projet de recherche. Les partenaires cliniques de ce projet sont des centres du CHU-Bordeaux et du CHU-Toulouse de renommée internationale sur MP et AMS.
Responsable du stage :Dr. Khalid Daoudi, équipe GeoStat (khalid.daoudi@inria.fr).
Lieu du stage : INRIA- Bordeaux Sud Ouest (http://www.inria.fr/bordeaux). Bordeaux, France.
Durée du Stage : 6 mois
Rémunération : 500euros/mois
Connaissances requises : De bonnes connaissances en traitement de la parole/signal ainsi qu'en programmation C++ et Matlab sont nécessaires. Des connaissances en apprentissage statistique (Machine learning) seraient un grand plus.
Les candidatures doivent être adressées à khalid.daoudi@inria.fr
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| 6-7 | (2017-01-22) Stage de 6 mois au LIA Avignon, France
Stage de 6 mois au LIA Avignon
Le stage que nous proposons se situe dans le cadre d?une collaboration entre la société MediaWen International et le Laboratoire d?Informatique d?Avignon (LIA). MediaWen propose des solutions en ligne pour le sous-titrage, la traduction et le doublage de vidéo sur le web. Une plate-forme de travail collaboratif inclut les différentes briques technologiques et permet d?accélérer ou d?automatiser les différents traitements.
Dans ce cadre, MediaWen et le LIA souhaitent explorer la faisabilité et l?intérêt d?une brique technologique autour de la détection automatique de la langue parlée. Les deux originalités majeures seront de pouvoir ajouter facilement une langue à partir d?un ensemble réduit d?exemples audio et de définir une stratégie interactive dans laquelle le critère à optimiser est le temps de travail de l?opérateur (à qualité de production identique).
L?objectif du stage proposé est de mettre en place cette brique en se basant sur la plate-forme ALIZE (développé en C++) qui a déjà donné lieu à plusieurs implémentations de systèmes de reconnaissance de la langue parlée.Une solution basée sur le paradigme des i-Vectors sera choisie. L?approche retenue sera dans un premier temps développée et testée en utilisant des données internes du laboratoire (notamment les données NIST) et en simulant les réponses de l?opérateur. Elle sera ensuite intégréedans les outils de MediaWen et testée sur les données correspondantes.
Une poursuite en thèse est envisageable selon le degré de la réussite de ce stage.
Le stagiaire sera encadré au LIA par Driss MATROUF (MCF-HDR) et Jean-François BONASTRE (Professeur). Il bénéficiera du soutien des spécialistes de MediaWen, pleinement associés au déroulé de ce stage.
Profil et Niveau :
Master en informatique, mathématiques ou traitement du signal. Un bon niveau en développement logiciel, dont la connaissance de C++, est requis.
Motivation, curiosité scientifique et rigueur seront des qualités demandées.
Durée :
5 à 6 mois (prolongation possible)
Rémunération :
~530 Euros/mois (indemnités légales pour un stage de niveau Master)
Contact:
driss.matrouf@univ-avignon.fr
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| 6-8 | (2017-01-27) Two R and D engineers at INRIA Nancy France
Our team at Inria Nancy is recruiting two R&D engineers for an ambitious industrial
project on voice processing in audiovisual contents. The mission is to develop, evaluate,
and improve software prototypes based on the latest scientific advances and transfer them
to the partner software development company and the sound creation studio which initiated
the project. The resulting commercial software will be a reference in the professional
audiovisual field.
*R&D engineer A*
Start date: May 2017
Duration: 18 months
Missions:
- speaker recognition based on ALIZE
- speech enhancement by multichannel deep learning
Profile:
- MSc or PhD in computer science, signal processing, or machine learning
- operational skills in software engineering (version control, tests, software quality)
and Python 3 language (numpy, scipy, Keras)
- experience in speaker recognition or speech enhancement would be a plus
Salary: 2048 to 2509? net/month depending on experience
*R&D engineer B*
Start date: May-June 2017
Duration: 16 months
Missions:
- speech recognition based on Kaldi
- concatenative speech synthesis
Profile:
- MSc or PhD in computer science, signal processing, or machine learning
- operational skills in software engineering (version control, tests, software quality)
and Python 3 (numpy, scipy, Keras) and Java (Java SE 8) languages
- experience in speech recognition or synthesis would be a plus
Salary: 2048 to 2509? net/month depending on experience
*Work environment*
Nancy is one of the top cities for young engineers in France with cheap accomodation, a
vibrant cultural scene, and good connections to Paris (1.5h), Luxemburg (1.5h), Belgium,
and Germany. Inria Nancy is a 500-people research institute dedicated to computer
science. The Multispeech team (https://team.inria.fr/multispeech/) is a 30-people group
covering various fields of speech science, with a strong emphasis on machine learning and
signal processing.
*To apply*
Send a CV, a motivation letter and 1 to 3 optional recommendation letters to
emmanuel.vincent@inria.fr. Mention which position(s) you are applying for. Applications
will be assessed on a rolling basis until March 17. Please apply as soon as possible
before that date.
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| 6-9 | (2017-02-01) Maitre de conférences, Ecole centrale Marseille France
L'Ecole Centrale Marseille ouvre un poste de Maitre de Conférences en
Informatique au concours 2017 dont le profil enseignement et recherche
est précisé ci-dessous (poste en cours de publication).
Liens utiles :
Ecole Centrale Marseille https://www.centrale-marseille.fr/
Laboratoire d?Informatique Fondamentale : http://www.lif.univ-mrs.fr/
=================================
Profil de poste MC en informatique à l?ECM
- Enseignement
Le/la maître de conférence recruté(e) devra être capable d?assurer un
enseignement attractif pour des élèves ingénieurs généralistes.
Il/elle aura vocation à s'intégrer au sein de l'équipe pédagogique
informatique pour assurer des enseignements de tronc commun
(Algorithmie, modélisation objet, stockage et traitement des données),
participer aux enseignants en informatique dans les options de
deuxième et troisième année, s?investir dans des proposer des projets
et suivre des groupes d'étudiants tout au long de leurs réalisations,
mais également participer à des actions de formation continue ou en
alternance. Il/elle jouera un rôle dans l'animation, la coordination
et l'évolution des enseignements, et participera aux actions
transverses multidisciplinaires de l'École Centrale Marseille.
Contacts : Pascal Préa (pascal.prea@centrale-marseille.fr)
- Recherche :
Le/la candidate devra en priorité développer des recherches dans le
cadre de projets initiés entre le Laboratoire d?Informatique
Fondamentale de Marseille (LIF) et l?Ecole Centrale Marseille (ECM).
Ces deux projets ont pour thèmes d?une part le traitement de données
massives, qu?il s?agisse de modèles de classification, d?optimisation
ou encore de visualisation, et d?autre part l?apprentissage profond,
l?apprentissage de représentations et les domaines d?applications
associés. Ces projets couvrent des thèmes relevant notamment des
équipes ACRO, BDA, QARMA et TALEP du LIF.
Au-delà de cette priorité thématique, toute candidature d?excellence
dans le périmètre du LIF est éligible.
Par ailleurs, la capacité du/de la candidat(e) à enrichir la dimension
technologique des recherches menées dans le cadre de ces projets et à
participer à des partenariats industriels est un plus incontestable.
Contact Recherche : Thierry Artières (thierry.artieres@centrale-marseille.fr)
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| 6-10 | (2017-02-13) CDD POST-DOCTORANT 18 mois *Analyse multimodale de contenus audiovisuels*
*CDD POST-DOCTORANT 18 mois*
*Analyse multimodale de contenus audiovisuels*
L?équipe LINKMEDIA (IRISA & Inria Rennes) travaille au développement des futurs
technologies permettant la description et l?accès aux contenus multimédias par le biais
de leur analyse. Les domaines de compétence de l?équipe sont la vision par ordinateur, le
traitement de la parole et du langage, le traitement des contenus audio, la recherche
d?information et la fouille de données. En particulier, l?équipe participe au projet FUI
NexGenTV portant sur l?analyse et l?enrichissement de contenus télévisés. La télévision
évolue de l?écran du téléviseur vers des applications multi-écrans où le spectateur
regarde la télévision tout en explorant le web, cherchant des compléments d?informations
ou réagissant sur les réseaux sociaux. Dans ce contexte, NexGenTV cherche à apporter des
solutions d?édition de contenus enrichis multi-écrans par le bais de fonctionnalités
telles la détection de temps forts, l?enrichissement de programmes par des informations
complémentaires et, plus généralement, l?optimisation de l?expérience utilisateur en
favorisant l?interaction adaptée aux attentes de l?utilisateur. Au sein du projet,
l?IRISA s?intéresse à l?analyse des contenus audiovisuels, de la parole et des réseaux
sociaux.
Dans ce contexte, nous souhaitons recruter un chercheur post-doctorant spécialisé dans
l?analyse de contenus audiovisuels pour développer, étudier et évaluer des approches
innovantes relatives à l?analyse des personnes au sein des contenus télévisés. On
cherchera notamment à concevoir des approches multimodales (voix+visage) permettant aussi
bien la détection de personnes connues que la mise en relation de vidéos d?un même
intervenant. Une première piste de travail s?appuie sur des travaux récents de l?équipe
en apprentissage de représentations multimodales à l?aide de réseaux neuronaux. On pourra
également étudier l?usage de ces derniers pour la représentation et la comparaison des
voix. Dans un second temps, on s?intéressera à l?exploitation de tels modèles pour
enrichir un contenu live avec des extraits de documents archivés, combinant
identification des intervenants et pertinence sémantique.
Les recherches envisagées seront menées dans l?équipe LINKMEDIA de l?IRISA (Rennes,
France), en collaboration étroite avec les partenaires du projet NexGenTV, notamment avec
EURECOM.
Le candidat devra posséder une thèse dans un domaine proche du sujet de recherche, de
préférence dans l?un des domaines suivants : modélisation multimodale, traitement
automatique de la parole, reconnaissance du locuteur, vision par ordinateur. On attend
également du candidat qu?il renforce la compétence de l?équipe en apprentissage neuronal
appliqué à l?analyse des contenus multimédia.
Pour candidater, merci d?adresser un CV accompagné d?une lettre de motivation.
Employeur : Centre National de la Recherche Scientifique
Lieu d?exercice : IRISA, Rennes
Contrat : CDD 18 mois, dès que possible à partir de mars 2017
Rémunération : 2 815? mensuels bruts
Contact : Guillaume Gravier (prenom.nom@irisa.fr)
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| 6-11 | (2017-02-20) Several possitions of Research Engineers at Audio Analytic Labs, Cambridge, UK
Audio Analytic Labs, the research division of Audio Analytic Ltd, has several Research
Engineer positions currently open in the field of Automatic Sound Recognition.
These could be of interest to your PhD students or Post-Docs finishing their contracts in
your teams and looking to follow up with an industrial position.
The complete job specification is copied below.
We are also open to answering questions from people interested in our company but not yet
available for employment.
More generally, we are open to finding concrete and mutually beneficial ways to
collaborate with academic partners on research projects, either through joint projects
supported by specific funding, or via secondments and internships.
For more information about our company, please visit the company?s website on
http://www.audioanalytic.com/ , or feel free to contact me directly.
I would be very grateful if you could propagate the attached job offer to your
institutions? career services, or if you could forward it directly to people who you
think may be directly interested in applying.
Hoping this will be useful, and of interest to your alumni.
Many thanks, and best regards,
- Sacha K.
Director of AALabs
AudioAnalytic Ltd.
INDUSTRIAL POSITION OPEN:
*Full Time Audio Analytics Research Engineer*
Location: Cambridge, Cambridgeshire, United Kingdom
Full-time, immediate start.
Audio Analytic Ltd. is leading the world of acoustically connected things. Our unique
software is used by smart home companies the world over to make devices aware of sounds
around them. If a smoke alarm goes off or a glass panel is broken by intruders while
no-one is at home, our software will immediately recognise the sound and tell the device
to alert the home owner and the smart home so they can both take appropriate protective
action. We give smart home owners sound peace of mind. More information is available on:
http://www.audioanalytic.com
We are looking for people who thrive as part of a dedicated and innovative team, love
tough challenges, and are passionate about audio/sound, DSP and Machine Learning.
Responsibilities
As part of our R&D team, you will contribute to researching and evaluating new algorithms
to push the limits of our unique sound recognition system. Responsibilities include
developing new algorithms in house, identifying and reporting on state of the art
methods, and evaluating both types of solutions on large scale field data sets.
Technical Skills
Must have either a Master?s degree with 2 years industrial experience or a PhD, in one of
the following topics: Digital Signal Processing of Audio Signals, Machine Learning
applied to Audio Signals, Automatic Speech/Speaker Recognition, Music Information
Retrieval, Acoustic Events Detection, Statistical Speech Synthesis, Thematic Indexing of
Audio tracks (e.g., Speaker Diarization, Acoustic Segmentation of Video Documents etc.).
Experience as a post-doc research engineer, either academic or industrial, will be a
significant plus.
Required:
Demonstrable skills in Digital Signal Processing and/or Machine Learning applied to
Audio Signals.
Demonstrable experience dealing with at least one type of Machine Learning algorithm
(e.g., Deep Neural Networks, Hidden Markov Models, Support Vector Machines, Decision
Trees etc.) applied to the processing of Audio Signals.
Scripting and algorithm prototyping: Python, bash.
Programming: C/C++ coding and code optimisation. CUDA/GPU programming a plus.
Development under Linux/Unix mandatory, Windows optional.
Desirable:
Hardware design knowledge a plus but not a requirement.
Demonstrable interest in porting DSP/Machine Learning algorithms to either embedded
platforms or high performance computing platforms a plus but not a requirement.
General Skills
Ability to deliver on research and evaluation methodology.
Good communication skills.
Excellent problem-solving skills.
Track record of academic publications a plus but not a requirement.
Enjoy working as a member of a team and using their own initiative.
Self-confident and highly motivated.
Ability to deal confidently with a variety of people at all levels.
Able to manage own workload and meet deadlines.
Good organisational skills.
Good standard of written and spoken English.
Remuneration
This is a great opportunity to join a successful company with a huge potential for
growth. The successful candidate will be compensated with an attractive package
appropriate to qualifications and experience, to include a competitive salary and stock
options.
How to Apply
To apply for this vacancy, please send a covering letter and copy of a recent CV to
jobs@audioanalytic.com, with reference AA-RES-ENG-2016 in the email title.
Please note that it is company policy not to accept job applications from recruitment
consultants.
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| 6-12 | (2017-02-21) Acting Assistant Professor, Department of Linguistics, University of Washington, WA, USA
Acting Assistant Professor, Department of Linguistics, University of Washington, Washington, USA, associated with the professional MS program and Ph.D. track in Computational Linguistics.
Application deadline: May 31, 2017, open until filled. Priority will be given to application received before March 1, 2017.
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| 6-13 | (2017-02-21) Several positions at Fluent.ai in Montreal, Canada
Fluent.ai is looking for both permanent full-time employees as well as interns. Please link this page: http://www.fluent.ai/careers/#toggle-id-3.
Fluent.ai is a startup based in Montreal, Canada. We are working on new deep learning and related techniques to enable acoustic-only speech recognition. By associating speech to intent without requiring a speech-to-text translation, Fluent.ai opens a wide variety of new applications and provides higher accuracy and more robust performance compared to existing methods. We are looking to expand our technology and research teams and are inviting applications for various permanent and internship based roles. Joining Fluent.ai provides you an opportunity to be an early team member leading work on an exciting, disruptive technology poised for rapid growth. The technology has already been validated by many academic experts as well as industrial customers in diverse sectors. Now we are looking for the right people to share our vision and hustle to achieve execution excellence in select sectors. You will be joining a diverse, dedicated, smart and fun team. We work hard, we don?t always agree, but we always laugh out loud and we always move forward together. What we offer: We offer a great working environment and a competitive mix of salary and options. We are keen to interact with talented people and will get back to the selected candidates quickly. We are an equal opportunity employer and value diversity at our company. We do not discriminate based on origin, religion, gender, age, sexual orientation, or disability. We are looking for both permanent full-time employees as well as interns. Please link this page: http://www.fluent.ai/careers/#toggle-id-3 Let me know if you have any questions, and I will be happy to answer those. About Fluent.ai Fluent.ai is a startup based in Montreal, Canada. We are working on new deep learning and related techniques to enable acoustic-only speech recognition. By associating speech to intent without requiring a speech-to-text translation, Fluent.ai opens a wide variety of new applications and provides higher accuracy and more robust performance compared to existing methods. We are looking to expand our technology and research teams and are inviting applications for various permanent and internship based roles. Joining Fluent.ai provides you an opportunity to be an early team member leading work on an exciting, disruptive technology poised for rapid growth. The technology has already been validated by many academic experts as well as industrial customers in diverse sectors. Now we are looking for the right people to share our vision and hustle to achieve execution excellence in select sectors. You will be joining a diverse, dedicated, smart and fun team. We work hard, we don?t always agree, but we always laugh out loud and we always move forward together. What we offer: We offer a great working environment and a competitive mix of salary and options. We are keen to interact with talented people and will get back to the selected candidates quickly. We are an equal opportunity employer and value diversity at our company. We do not discriminate based on origin, religion, gender, age, sexual orientation, or disability.
Vikrant Tomar
Fluent.ai
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| 6-14 | (2017-02-22) Language modeling scientist at Siri team at Apple
Title: Language Modeling Scientist – Siri Speech team at Apple
Job Summary
Play a part in the next revolution in human-computer interaction. Contribute to a product that is redefining mobile computing. Create groundbreaking technology for large scale systems, spoken language, big data, and artificial intelligence. And work with the people who created the intelligent assistant that helps millions of people get things done — just by asking. Join the Siri Speech team at Apple.
The Siri team is looking for exceptionally skilled and creative Scientists and Engineers eager to get involved in hands-on work improving the Siri experience.
Key Qualifications
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Experience building, testing, and tuning language models for ASR
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Ability to implement experiments using scripting languages (Python, Perl, bash) and tools written in C/C++
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Experience working with standard speech recognition toolkits (such as HTK, Attila, Kaldi, SRILM, OpenFST or equivalent proprietary systems)
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Large scale data analysis experience using distributed clusters (e.g. MapReduce, Spark)
Description
The speech team is seeking a research scientist to participate in the language modeling effort for Siri. In order to estimate language model probabilities, you will make use of very large amounts of training text drawn from diverse sources. You will be part of a group that has responsibility for the entire domain of language modeling in multiple languages including, among other things, text processing, data selection, language model adaptation, neural network modeling, improving language model training infrastructure, experimenting with new types of language models etc.
Education
PhD or Masters in Computer Science or related field
3+ years of experience in language modeling for ASR
Apply online at jobs.apple.com
Search for: “Language Modeling Scientist”
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| 6-15 | (2017-02-28) Postdoctoral Researcher (Speech/Audio Processing), University of Eastern Finland, Joensuu Campus, Finland
*****
Postdoctoral Researcher (Speech/Audio Processing) |
|
The University of Eastern Finland, UEF, is one of the largest multidisciplinary universities in Finland. We offer education in nearly one hundred major subjects, and are home to approximately 15,000 students and 2,800 members of staff. We operate on three campuses in Joensuu, Kuopio and Savonlinna. In international rankings, we are ranked among the leading 300 universities in the world.
The Faculty of Science and Forestry operates on the Kuopio and Joensuu campuses of the University of Eastern Finland. The mission of the faculty is to carry out internationally recognised scientific research and to offer research-education in the fields of natural sciences and forest sciences. The faculty invests in all of the strategic research areas of the university. The faculty?s environments for research and learning are international, modern and multidisciplinary. The faculty has approximately 3,800 Bachelor?s and Master?s degree students and some 490 postgraduate students. The number of staff amounts to 560. http://www.uef.fi/en/lumet/etusivu
We are now inviting applications for
a Postdoctoral Researcher (Speech/Audio Processing), School of Computing, Joensuu Campus
The Machine Learning research group of the School of Computing at the University of Eastern Finland (http://www.uef.fi/en/web/cs) is looking for a highly motivated researcher to work in the group.
The current research topics in the group include speaker and language recognition, voice conversion, spoofing and countermeasures for speaker recognition, robust feature extraction, and analysis of environmental sounds. Prior experience in these topics is a plus, though we invite candidates widely from general speech/audio/language processing, machine learning or signal processing background. We expect the new Postdoctoral Researcher to bring in complementary skills and expertise.
The recruited Postdoctoral Researcher will take a major role in advancing research in one of the above-listed (or closely related) topics. He or she will also have a significant role in the supervision of students and certain administrative duties, and he or she will work closely with Associate Professor Kinnunen and the other members of the group. The position is strongly research-focused.
The School of Computing, located in Joensuu Science Park, provides modern research facilities with access to high-performance computing services. Our research group hosted the Odyssey 2014 conference (http://cs.uef.fi/odyssey2014/), is a partner in the ongoing H2020 funded OCTAVE project (https://www.octave-project.eu/) focused on voice biometrics, is a co-founder of the Automatic Speaker Verification and Countermeasures (ASVspoof) challenge series (http://www.spoofingchallenge.org/) and has hosted international summer schools. We take actively part in international benchmarking and other collaboration activities. We follow a multidisciplinary research perspective that targets at understanding the speech signal, as well as applying the acquired knowledge to new application areas.
A person to be appointed as a postdoctoral researcher shall hold a suitable doctoral degree that has been awarded less than five years ago. The doctoral degree should be in spoken language technology, electrical engineering, computer science, machine learning or a closely related field. He/she should be comfortable with Unix/Linux, Matlab/Octave and/or Python, processing of large datasets and with strong hands-on experience and creative out-of-the-box problem solving attitude.
The position will be filled from May 1, 2017 until December 31, 2018. The continuation of the position will be agreed separately.
The positions of postdoctoral researcher shall always be filled for a fixed term (UEF University Regulations 31 §).
The salary of the position is determined in accordance with the salary system of Finnish universities and is based on level 5 of the job requirement level chart for teaching and research staff (?2.865,30/ month). In addition to the job requirement component, the salary includes a personal performance component, which may be a maximum of 46.3% of the job requirement component.
For further information on the position, please contact: Associate Professor Tomi Kinnunen, email: tkinnu@cs.uef.fi, tel. +358 50 442 2647. For further information on the application procedure, please contact: Executive Head of Administration Arja Hirvonen, tel. +358 44 716 3422, email: arja.hirvonen@uef.fi.
A probationary period is applied to all new members of the staff.
The electronic application should contain the following appendices:
- a cover letter indicating the position to be applied for and a free-worded motivation letter
- a résumé or CV
- a list of publications
- copies of the applicant's academic degree certificates/ diplomas, and copies of certificates / diplomas relating to the applicant?s language proficiency, if not indicated in the academic degree certificates/diplomas
- the names and contact information of at least two referees
The application needs to be submitted no later than March 24, 2017 (by 24:00 EET) by using the electronic application form:
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| Apply for the job |
The job ad and the application form can also be located under http://www.uef.fi/en/uef/en-open-positions (seek for the position 'Postdoctoral Researcher (Speech/Audio Processing)'). |
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| 6-16 | (2017-02-28) MCF en informatique pour les Sciences Humaines, Sorbonne, Paris, France
Un poste de MCF en informatique pour les Sciences Humaines, notamment en traitement automatique du langage et/ou de la parole, est ouvert à l'Université Paris Sorbonne (www.paris-sorbonne.fr/IMG/pdf/27-7_mcf_766.pdf). Le candidat enseignera l'Informatique dans les différentes formations de licence et de master du département d'Informatique, Mathématiques et de Linguistique appliquées de l'UFR de Sociologie et d'Informatique pour les Sciences Humaines. Il devra s'inscrire dans un ou plusieurs axes de l'équipe de linguistique computationnelle (www.stih.paris-sorbonne.fr/) : (1) Sémantiques, connaissances et corpus (2) Paralinguistique, cognition et physiologie.
Personne à contacter : Claude.Montacie@Paris-Sorbonne.fr
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| 6-17 | (2017-03-14) PhD and postdocs positions at INRIA/Nancy France
Our team has several openings for PhD students and postdocs in the fields of deep learning based: - speech enhancement - speech recognition - environmental sound analysis For details and to apply, see:https://team.inria.fr/multispeech/category/job-offers/ Application deadline: - April 15 for postdoctoral positions - April 30 for PhD positions --
Emmanuel Vincent
Multispeech Project-Team
Inria Nancy - Grand Est
615 rue du Jardin Botanique, 54600 Villers-lès-Nancy, France
Phone: +33 3 8359 3083 - Fax: +33 3 8327 8319
Web: http://members.loria.fr/evincent/
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| 6-18 | (2017-03-18) Fully-funded PhD Positions in Automatic Emotion Recognition at SUNY, Albany, NY, USA
Fully-funded PhD Positions in Automatic Emotion Recognition at SUNY
Application deadline: 22 March 2017 (**see below for more information**)
We have several PhD research assistantship positions available at the State University of New York, Albany. We are seeking highly creative and motivated applicants with a keen interest in doing research in human-centered technology, affective computing, and automatic emotion recognition using machine learning and multimodal signal processing techniques.
Requirements: - A bachelor's degree in a relevant field (Electrical and Computer Engineering, Computer Science, Statistics, or related) - Solid background in computer programming - Proficiency in spoken and written English - (Preferred) Knowledge in the following technologies: MATLAB, Python, Java, Perl, C++, Unity - (Preferred) Previous coursework and/or practical experience in machine learning - (Preferred) Solid background in mathematics and/or statistics Interest in one of the following areas: - Human-Centered and Affective Computing, Computational Human Behavior Analysis - Machine Learning, Statistics, Applied Mathematics - Speech Processing, Computer Vision
We expect: - Keen interest in top level conference and journal publications - Self-organized, team worker, with good communication skills
We offer: - You will work at one of the leading U.S. Universities and have the opportunity to work towards your PhD in a group of excellent scientists - Tuition, stipend, and fringe benefits - You will get financial support to attend and present at top level international conferences - Visas will be fully funded for international students
To apply, please send an email to Prof. Yelin Kim (yelinkim@albany.edu) including a CV and a research statement (max. 2 pages) by March 22, 2017. We have rolling admissions policies, so please apply as early as possible. Please give your email the subject “SUNY PhD Research Assistantship in Automatic Emotion Recognition.'
Please liberally forward and share to possibly interested candidates or people that might know suitable candidates.
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| 6-19 | (2017-03-20) Ph D position at IRISA Rennes, France
The Expression team of IRISA is recruiting a PhD candidate in computer science on the subject 'Universal speech synthesis through embeddings of massive heterogeneous data'. This work focuses on the following domains:
- Text-to-speech
- Deep learning
- High-dimensional indexing.
Details are given here: http://www.irisa.fr/en/offres-theses/universal-speech-synthesis-through-embeddings-massive-heterogeneous-data .
Application deadline: Monday, 3 April 2017.
Application process:
- CV
- Transcript of M.Sc. marks/grades
- to gwenole.lecorve@irisa.fr, damien.lolive@irisa.fr, laurent.amsaleg@irisa.fr .
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| 6-20 | (2017-03-25) Offre de thèse en Systèmes d'interaction vocale , LIA, Avignon France
***** Offre de thèse en Systèmes d?interaction vocale *****
au LIA/CERI Univ. Avignon Prof. F. Lefèvre et B. Jabaian
Améliorer l'interaction vocale avec le monde numérique et la conception
de nouveaux services de dialogue homme-machine sont des défis essentiels
pour un passage total vers une société numérique. Parmi les activités de
recherche en intelligence artificielle portant sur les interactions
vocales, plusieurs questions importantes sont encore mal examinées et
peuvent faire l?objet de différentes études. Le LIA traite de multiples
aspects liés à l?interaction vocale et cherche à travers cette thèse à
approfondir la recherche dans l?une des ces grandes problématiques parmi :
** Le dialogue argumentatif **
pour rendre les systèmes artificiels capables d'apprendre à partir des
données, deux hypothèses fortes sont généralement faites : (1) la
stationnarité du système : on suppose que l'environnement de la machine
ne changera pas avec le temps. (2) l'interdépendance entre la collecte
des données et le processus d'apprentissage : cela implique que
l'utilisateur ne modifie pas son comportement dans le temps alors que ce
dernier a tendance à adapter son comportement en fonction de la réaction
de la machine. Il est clair que ce comportement n'aide pas un système
d'apprentissage artificiel à trouver l'équilibre lui permettant de
satisfaire au mieux les attentes de l'utilisateur.
Les interfaces vocales actuelles, basées sur des processus de décision
markovien partiellement observables, doivent évoluer vers une nouvelle
génération de systèmes interactifs, capables d'apprendre dynamiquement à
partir d'interactions sur le long terme, tout en tenant compte que le
comportement des humains est variable, étant eux-mêmes des systèmes
adaptatifs. En effet, les humains apprennent également de leurs
interactions avec un système et changent leur comportement au cours du
temps. Un tel système sera capable de discuter avec l?humain et
argumenter pour défendre ses choix.
** L?agent dialoguant autoritaire **
L'intelligence artificielle est généralement vue à travers sa soumission
aux désirs/volontés de l'humain, il existe toutefois des situations où
artificiellement doter la machine d'une dimension autoritaire peut être
pertinent (games et serious games principalement, mais aussi simulation
de contrôle...). Des mécanismes concrets permettant de développer un
agent autoritaire (dans l'objectif d'imposer son point de vue à
l'utilisateur) seront étudiés et mis en oeuvre en pratique pour
permettre leur évaluation complète.
** La réalité virtuelle pour la simulation d'agents dialoguant **
Une autre piste de recherche concerne les possibilités offertes par la
réalité virtuelle pour permettre l'apprentissage d'agent vocaux
dialoguant. L'objectif initial est d'offrir un cadre unifié pour le
développement en conditions d'utilisation de systèmes de dialogue situés
par le biais de simulations en réalité virtuelle des environnements
envisagés, éliminant ainsi la nécessité de les recréer. A terme
l'approche permettra aussi de développer des systèmes de dialogue pour
les applications de réalité virtuelle elle-mêmes. Le travail implique
donc des compétences dans les deux domaines de la réalité virtuelle et
du traitement automatique du langage.
Le candidat doit avoir un master en informatique avec une composante sur
les méthodes d'apprentissage automatique et/ou sur l?ingénierie de la
langue. La bourse de thèse fera l?objet d?un concours au sein de l?Ecole
Doctorale 536 de l?université d?Avignon, avec une audition du candidat
retenu par les encadrants de thèse.
Pour postuler merci d?envoyer un mail avant le 30 avril 2017 à Fabrice
Lefèvre (fabrice.lefevre@univ-avignon.fr) et Bassam Jabaian
(bassam.jabaian@univ-avignon.fr) incluant : votre CV, une lettre de
motivation avec votre positionnement sur les propositions d?études
ci-dessus, d?éventuelles lettres de recommandation et vos relevés de notes.
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| 6-21 | (2017-03-28) Research Scientist, Spoken and Multimodal Dialog Systems, ETS, S.Francisco, CA, USA
Open Rank Research Scientist, Spoken and Multimodal Dialog Systems
ETS (Educational Testing Service) is a global not for profit organization whose mission is to advance quality and equity in education. With more than 3,400 global employees, we develop, administer and score more than 50 million tests annually in more than 180 countries.
Our San Francisco Research and Development division is seeking a Research Scientist for our Dialog, Multimodal, and Speech (DIAMONDS) research center. The center’s main focus is on foundational research as well as on development of new capabilities to automatically score spoken, interactive, and multimodal test responses in conversational settings in a wide range of ETS test programs, promote learning and other educational areas. This is an excellent opportunity to be part of a world-renowned research and development team and have a significant impact on existing and next generation spoken and multimodal dialog systems and their application to assessment and other areas in education.
Primary responsibilities include:
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Developing and collaborating on interdisciplinary projects that aim to transfer techniques to a new context or scientific field. Successful candidates are self-motivated and self-driven, and have a strong interest in emerging conversational technology that can contribute to education in assessment and instructional settings.
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Providing scientific and technical skills to conceptualize, design, obtain support for, conduct, and manage new research projects, grants, or parts of existing projects.
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Generating or contributing to new or modified methods that support research on and development of spoken and multimodal dialog systems and related technologies relevant in assessment and instructional settings.
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Designing and conducting scientific studies and functioning as an expert in the major facets of the projects: responding as a subject matter expert in presenting the results of acquired knowledge and experience.
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Developing or assisting in developing proposals for external and internal research grants and obtain financial support for new or continuing research activities. Prepare initial and final proposal and project budgets.
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Participating in dissemination activities through the publications of research papers in peer-reviewed journals and in the ETS Research Report series, the issuing of progress and technical reports, the presentation of seminars at major conferences and at ETS, or the use of other appropriate communication vehicles, including patents, books and chapters, that impact practice in the field or at ETS.
Depending on experience this position is open to entry level candidates as well as mid-level and senior level professionals.
REQUIREMENTS FOR A JUNIOR LEVEL POSITION
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A Doctorate in computer science, linguistics, cognitive psychology or a related field is required. One year of research experience is required, in education is desirable. Experience can be gained through doctoral studies. Candidates should be very skilled in programming and be able to work effectively as a research team member.
REQUIREMENTS FOR A MID-LEVEL POSITION
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A Doctorate in computer science, linguistics, cognitive psychology, or a related field is required. Research experience in education is desirable. Candidates should be very skilled in programming and be able to work effectively as a research team member. Three years of progressively independent substantive research in the area of computer science, linguistics, cognitive psychology, or education are required.
REQUIREMENTS FOR A SENIOR-LEVEL POSITION
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A Doctorate in computer science, linguistics, cognitive psychology, or a related field is required. Research experience in education is desirable. Candidates should be very skilled in programming and be able to work effectively as a research team member. Eight years of progressively independent substantive research in the area of computer science, linguistics, cognitive psychology, or education are required.
We offer a competitive salary, comprehensive benefits and excellent opportunities for professional and personal growth. For a full list of position responsibilities and to apply please visit the following link: http://ets.pereless.com/careers/index.cfm?fuseaction=83080.viewjobdetail&CID=83080&JID=235623&BUID=2538
ETS is an Equal Opportunity Employer
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| 6-22 | (2017-04-10) 3 Funded PhD Research Studentships at CSTR, Edinburgh, Scotland, UK
Three Funded PhD Research Studentships at the Centre for Speech Technology Research,
University of Edinburgh.
Please see http://www.cstr.ed.ac.uk/opportunities for full details, eligibility
requirements, application procedure and deadlines.
1. Embedding enhancement information in the speech signal
Speech becomes harder to understand in the presence of noise and other distortions, such
as telephone channels. This is especially true for people with a hearing impairment. It
is difficult to enhance the intelligibility of a received speech+noise mixture, or of
distorted speech, even with the relatively sophisticated enhancement algorithms that
modern hearing aids are capable of running. A clever way around this problem might be for
the sender to add extra information to the original speech signal, before noise or
distortion is added. The receiver (e.g., a hearing aid) would use this to assist speech
enhancement.
Funding: Marie Sklodowska-Curie fellowship
2. Broadcast Quality End-to-end Speech Synthesis
Advances in neural networks made jointly in the fields of automatic speech recognition
and speech synthesis, amongst others, have led to a new understanding of their
capabilities as generative models. Neural networks can now directly generate synthetic
speech waveforms, without the limited quality of a vocoder. We have made separate
advances, using neural networks to discover representations of spoken and written
language that have applications in lightly-supervised text processing for almost any
language, and for adaptation of speaker identity and style. The project will combine
these techniques into a single end-to-end model for speech synthesis. This will require
new techniques to learn from both text and speech data, which may have other
applications, such as automatic speech recognition.
Funding: EPSRC Industrial CASE award (in collaboration with the BBC)
3. Automatic Extraction of Rich Metadata from Broadcast Speech (in collaboration with the
BBC)
The research studentship will be concerned with automatically learning to extract rich
metadata information from broadcast television recordings, using speech recognition and
natural language processing techniques. We will build on recent advances in
convolutional and recurrent neural networks, using architectures which learn
representations jointly, considering both acoustic and textual data. The project will
build on our current work in the rich transcription of broadcast speech using neural
network based speech recognition systems, along with neural network approaches to machine
reading and summarisation. In particular, we are interested in developing approaches to
transcribing broadcast speech in a way appropriate to the particular context. This may
include compression or distillation of the content (perhaps to fit in with the
constraints of subtitling), transforming conversational speech into a form that is more
easy to read as text, or transcribing broadcast speech in a way appropriate for a
particular reading age.
Funding: EPSRC Industrial CASE award (in collaboration with the BBC)
--
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| 6-23 | (2017-04-11) Postdoctoral research position, Univ. Stellenbosch, South Africa
Postdoctoral research position: Multitlingual code-switched speech corpus and systems
A postdoc position focussing on corpus compilation and automatic speech recognition of codeswitched South African speech in several languages is available in the Digital Signal Processing Group of the Department of Electrical and Electronic Engineering at the University of Stellenbosch, South Africa.
The project will involve the compilation of a multilingual (at least 5 languages) corpus of conversational code-switched South African speech. It will also include the development of associated automatic speech recognition systems able to process this speech. Specific project objectives include the gathering of the acoustic data, developing a transcription protocol, recruiting annotators, setting up and managing the annotation process, developing a validation protocol, validating the data, developing baseline automatic speech recognition systems in the languages of the corpus, and producing new and original research into how best to automatically recognise and process this mixed-language speech.
Applicants must hold a PhD (preferably obtained within the last 5 years) in the field of Electronic/Electrical Engineering, Information Engineering, Computer Science, or other relevant discipline. Suitable candidates must also have practical and research experience with automatic speech processing systems in general and multilingual automatic speech recognition in particular, and should have an excellent background in statistical modelling, signal processing, and/or speech analysis. Applicants should also have proven prior experience in speech corpus compilation, have good programming skills and be able to use high level programming languages for developing prototype systems. Finally, candidates must have excellent English writing skills and have an explicit interest in scientific research and publication.
The position will be available for one year, with a possible extension to a second and third year, depending on progress and available funds.
Applications should include a covering letter, curriculum vitae, list of publications, research projects, conference participation and details of three contactable referees and should be sent as soon as possible to: Prof Thomas Niesler, Department of Electrical and Electronic Engineering, University of Stellenbosch, Private Bag X1, Matieland 7602. Applications can also be sent by email to: trn@sun.ac.za. The successful applicant will be subject to University policies and procedures.
Interested applicants are welcome to contact me at the above e-mail address for further information regarding the project.
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| 6-24 | (2017-04-20) Postdoc for project LaDyCa, Sorbonne, Paris
Applicants must have a PhD in linguistics as well as publications in their field of specialization. Independent research experience in one or several of the core areas of the LaDyCa project (i.e. language dynamics, linguistic typology, sociolinguistics, geolinguistics, dialectology & dialectometry) is expected. An experience in working with scholars of diverse backgrounds, e.g. linguists, sociologists, anthropologists, historians and, to some extent, mathematicians or statisticians would be greatly appreciated.The project will be funded by the IDEX (?Initiative d?Excellence?) consortium of Sorbonne Universités, France, in partnership with Ilia State University, Tbilisi, Georgia. Apart from an efficient and fluent command of English and/or French, for collegial relations. with an international team of scholars, applicants should have a good command of Georgian (written & oral skills); efficient reading skills in Russian would be an asset too. A good command of database software, and previous training or experience in computational linguistics would be also appreciated. A strong performing ability in entering data and in designing linguistic databases would be an asset.
Applications should include a statement of interest (letter of motivation), giving accurate details on the applicant?s skills corresponding to the aim of the LaDyCa project, and
how (s)he plans to process data with computing tools and gather information on the ecological, historical and social context of linguistic diversity in the Caucasus. (S)he will also
provide a CV including a list of publications, a copy of the PhD certificate, and the names and e-mail addresses of two referees. Applications should be sent as a single PDF file to the e-
mail addresses below, entitled ?Application_LaDyCa_PostDoc?:
Prof. Jean Léo Léonard < leonardjeanleo@gmail.com >
Prof. Claude Montacié < Claude.Montacie@paris-sorbonne.fr >
Deadline: applications must be submitted by 2 nd of May 2017.
The position is available from July 2017 to June 2018.The duration of employment is intended to last one year.
Net salary: around 2100 euros per month.
http://www.stih.paris-sorbonne.fr/?p=1203
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| 6-25 | (2017-04-22) Poste d'ATER à Paris Sorbonne, France
un poste d'ATER en Traitement automatique des langues et de la Parole est disponible à
l'Université Paris-Sorbonne. Le lien pour postuler est
http://concours.univ-paris4.fr/PostesAter?entiteBean=posteCandidatureCourant&modif=839.
Les conditions pour candidater sont disponibles sur www.paris-sorbonne.fr/ater
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| 6-26 | (2017-04-23) Associate research scientist-Speech at ETS, Princeton, New Jersey, USA
http://ets.pereless.com/careers/index.cfm?fuseaction=83080.viewjobdetail&CID=83080&JID=243925&type=&cfcend
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| 6-27 | (2017-05-02) PhD at IRISA, Rennes, France
L'équipe Expression de l'IRISA ouvre un poste de doctorant en informatique sur le sujet 'caractérisation de registres de langue par extraction de motifs séquentiels' dans le cadre du projet ANR TREMoLo.
Domaines : traitement automatique des langues et fouille de données.
Détails de l'offre : http://www.irisa.fr/fr/offres-theses/caracterisation-registres-langue-extraction-motifs-sequentiels
Date limite de candidature : vendredi 2 juin.
Dossier de candidature (* : éléments obligatoires) :
- CV détaillé*
- lettre de motivation*
- relevés de notes (avec classement si possible)*
- contacts pour recommandation*
- rapport(s) de stage recherche (si applicable).
Envoyer à : del.battistelli@gmail.com, nicolas.bechet@irisa.fr, gwenole.lecorve@irisa.fr.
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| 6-28 | (2017-05-05) Post-doctoral positions in Multimodal Behavior Analysis: Speech, Vision and Healthcare, CMU, Pittsburgh, PA, USA
Post-doctoral positions in Multimodal Behavior Analysis: Speech, Vision and Healthcare
Carnegie Mellon University, School of Computer Science
Multiple post-doctoral positions are available in the School of Computer Science at Carnegie Mellon University. We are seeking creative and energetic applicants for two-year postdoctoral positions. The positions include a competitive salary with full benefits and travel resources.
Candidates must have a strong research track record for one or more of the following topics: (1) speech and paralinguistic processing for affect, emotion and human behavior analysis, (2) automatic recognition of facial expressions, gestures and human visual activities, (3) multimodal machine learning algorithms for text, audio and video, (4) technologies to help clinicians with mental health diagnoses and treatments.
Required
- PhD in computer science or related field (at the time of hire)
- International applicants welcome! No US citizenship requirement.
Desired
- Publications in top machine learning, speech processing and/or computer vision conferences and journals.
- Research involving clinical patients with mental health disorders (e.g., depression, schizophrenia, suicidal ideation)
- Experience mentoring graduate and undergraduate students
Job details
- Preferred start date: September 1st, 2017 (negotiable)
- Candidate will work under the supervision of Dr. Louis-Philippe Morency, CMU MultiComp Lab’s director
- Competitive salary with full benefits and travel resources.
How to apply
- Email applications should be sent to morency@cs.cmu.edu with the title “Postdoc application”, preferably before June 12th, 2017. The email should include:
- a brief cover letter (with expected date of availability),
- a CV including list of publications,
- contact information of two references,
- links to three representative publications
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| 6-29 | (2017-05-10) CDI Ingénieur docteur en informatique ou sciences du langage, LNE, Trappes, France
Ingénieur docteur en informatique ou sciences du langage
CDI – TRAPPES
Référence:AP/TAI/DE
L’entreprise: WWW.LNE.FR
Leader dans l’univers de la mesure et des références, jouissant d’une forte notoriété en France et à l’international, le LNE soutient l’innovation industrielle et se positionne comme un acteur important pour une économie plus compétitive et une société plus sûre. Au carrefour de la science et de l’industrie depuis sa création en 1901, le LNE offre son expertise à l’ensemble des acteurs économiques impliqués dans la qualité et la sécurité des produits.
Pilote de la métrologie française, notre recherche est au cœur de notre mission de service public et constitue un facteur fondamental au soutien de la compétitivité des entreprises.
Nous avons à cœur de répondre aux exigences des industriels et du monde académique, pour des mesures toujours plus justes, effectuées dans des conditions de plus en plus extrêmes ou sur des sujets innovants tels que les véhicules autonomes, les nanotechnologies ou la fabrication additive.
Le LNE en quelques chiffres: 700 collaborateurs.
5 métiers (la mesure, les essais, la certification, la formation et la R&D).
8 domaines d’intervention (Métrologie, Santé, Bâtiment, Environnement, Energie, Transports, Sécurité et Défense, Biens de consommation).
55 000 m2 de laboratoires (dont 10 000m2 à Paris et 45 000m2 à Trappes).
7 implantations (2 sites en Ile de France, 2 délégations régionales à Poitiers et Nîmes, 1 antenne à St Etienne, 2 filiales à Washington, Hong Kong).
9000 clients.
Missions :
Le docteur sera intégré à une équipe de 4 ingénieur-docteurs qui encadrent différents stagiaires et doctorants. Cette équipe est historiquement spécialiste de l’évaluation des systèmes de traitement de l’information multimédia (transcription de parole, reconnaissance du locuteur, dialogue, traduction…). Elle s’ouvre aujourd’hui à de nouveaux enjeux que sont l’évaluation des systèmes d’intelligence artificielle en général (robotique, smart-grid, domaine de la défense, véhicule autonome…).
Le docteur se verra attribuer les missions suivantes :
Profil :
Titulaire d’un doctorat en Informatique ou Sciences du langage, vous avez des compétences en traitement automatique de la langue ou en linguistique de corpus. Vous maitrisez également la programmation (R ou S, C++, PYTHON).
Vous êtes doté de bonnes qualités rédactionnelles et relationnelles. Vous avez une bonne communication orale et vous aimez travailler en collaboration avec votre équipe et les clients.
Vous avez un anglais vous permettant une communication professionnelle.
Déplacements en région parisienne, 1 jour par semaine et dans le monde 1 fois par an.
Pour déposer votre candidature :envoyer CV+LM à recrut@lne.fr – réf AP/TAI/DE
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| 6-30 | (2017-05-10) Open Rank Research Scientist, Spoken and Multimodal Dialog Systems, ETS, San Francisco, CA, USA
Open Rank Research Scientist, Spoken and Multimodal Dialog Systems
ETS (Educational Testing Service) is a global not for profit organization whose mission is to advance quality and equity in education. With more than 3,400 global employees, we develop, administer and score more than 50 million tests annually in more than 180 countries.
Our San Francisco Research and Development division is seeking a Research Scientist for our Dialog, Multimodal, and Speech (DIAMONDS) research center. The center’s main focus is on foundational research as well as on development of new capabilities to automatically score spoken, interactive, and multimodal test responses in conversational settings in a wide range of ETS test programs, promote learning and other educational areas. This is an excellent opportunity to be part of a world-renowned research and development team and have a significant impact on existing and next generation spoken and multimodal dialog systems and their application to assessment and other areas in education.
Primary responsibilities include:
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Developing and collaborating on interdisciplinary projects that aim to transfer techniques to a new context or scientific field. Successful candidates are self-motivated and self-driven, and have a strong interest in emerging conversational technology that can contribute to education in assessment and instructional settings.
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Providing scientific and technical skills to conceptualize, design, obtain support for, conduct, and manage new research projects, grants, or parts of existing projects.
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Generating or contributing to new or modified methods that support research on and development of spoken and multimodal dialog systems and related technologies relevant in assessment and instructional settings.
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Designing and conducting scientific studies and functioning as an expert in the major facets of the projects: responding as a subject matter expert in presenting the results of acquired knowledge and experience.
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Developing or assisting in developing proposals for external and internal research grants and obtain financial support for new or continuing research activities. Prepare initial and final proposal and project budgets.
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Participating in dissemination activities through the publications of research papers in peer-reviewed journals and in the ETS Research Report series, the issuing of progress and technical reports, the presentation of seminars at major conferences and at ETS, or the use of other appropriate communication vehicles, including patents, books and chapters, that impact practice in the field or at ETS.
Depending on experience this position is open to entry level candidates as well as mid-level and senior level professionals.
REQUIREMENTS FOR A JUNIOR LEVEL POSITION
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A Doctorate in computer science, linguistics, cognitive psychology or a related field is required. One year of research experience is required, in education is desirable. Experience can be gained through doctoral studies. Candidates should be very skilled in programming and be able to work effectively as a research team member.
REQUIREMENTS FOR A MID-LEVEL POSITION
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A Doctorate in computer science, linguistics, cognitive psychology, or a related field is required. Research experience in education is desirable. Candidates should be very skilled in programming and be able to work effectively as a research team member. Three years of progressively independent substantive research in the area of computer science, linguistics, cognitive psychology, or education are required.
REQUIREMENTS FOR A SENIOR-LEVEL POSITION
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A Doctorate in computer science, linguistics, cognitive psychology, or a related field is required. Research experience in education is desirable. Candidates should be very skilled in programming and be able to work effectively as a research team member. Eight years of progressively independent substantive research in the area of computer science, linguistics, cognitive psychology, or education are required.
We offer a competitive salary, comprehensive benefits and excellent opportunities for professional and personal growth. For a full list of position responsibilities and to apply please visit the following link: http://ets.pereless.com/careers/index.cfm?fuseaction=83080.viewjobdetail&CID=83080&JID=235623&BUID=2538
ETS is an Equal Opportunity Employer
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| 6-31 | (2017-05-10) Research Scientist, Disney Research, Pittsburgh, PA, USA
Position: Research Scientist
Focus Area: Autonomous Agents for Multimodal Character Interaction
Disney Research
Disney Research Pittsburgh is seeking applicants for a Research
Scientist position, at either the junior or senior level, in
Autonomous Agents. The research emphasis is on architecture to support
the integration of natural language with character-based reasoning and
behavior.
As part of The Walt Disney Company, Disney Research builds upon a rich
legacy of innovation and technology leadership in the entertainment
industry that continues to this day. Disney Research was launched in
2008 offering the best attributes of academia and industry with the
goal of driving value across the company through technological
innovation. Our research covers a broad range of exciting and
challenging applications that are experienced daily by millions of
people around the world.
Our staff interacts directly with all core business areas of The Walt
Disney Company including Theme Parks and Imagineering, Consumer
Products, our Live Action and Animation Studios, and Media Networks.
We publish our research and are actively engaged with the global
research community. Our researchers collaborate closely with
co-located academic institutions.
We are seeking applicants in the following areas:
· Agent architectures for language-based character interaction.
· AI and machine learning methods for autonomous,
semantically-rich character behavior
Duties:
· Drive value for Disney through groundbreaking research and innovation
· Lead a research group with post-doctoral researchers,
interns, and external collaborators
· Publish results and patent inventions in multimodal interaction
· Participate in conferences, workshops and academic-industrial events
· Develop a strong network of business partners within the company
Required Qualifications:
· Ph.D. in Computer Science or equivalent
· Proven track record of developing autonomous, integrated
agents with real-time NL components.
· Experience with both symbolic and statistical machine
learning methods as applied to modeling semantics, action, or behavior
· Possess strong technical presentation skills and able to
clearly communicate with technical and non-technical audiences
Desired Qualifications:
· Experience in interaction design for entertainment
· Background in NLP (e.g., relationship extraction, word sense
disambiguation, narrative generation) desirable
To apply:
Please email careers@disneyresearch.com. Please use DRP-RS-NLP-2017 in
your subject line. If you're interested in the position or for any
further information, please contact Jill Lehman
(jill.lehman@disneyresearch.com).
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