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ISCApad #210 |
Sunday, December 13, 2015 by Chris Wellekens |
6-1 | (2015-07-01) A 3 year fully-funded PhD studentship at University of Sheffield, UK We have a 3 year fully-funded PhD studentship in the use of Spoken Language Dialogue Systems in Assistive Technology. Full details are at http://www.sheffield.ac.uk/dcs/resdegrees/funded_phds Closing date is 16th August 2015. Please circulate to suitable candidates.
Lecturer, Department of Computer Science, University of Sheffield Centre for Assistive Technology and Connected Healthcare (http://www.catch.org.uk/)
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6-2 | (2015-07-20) Post-Doctoral Researcher at the Advanced Digital Sciences Center, Singapore -------------------------------------------------------------
WHO: Post-Doctoral Researcher wanted
WHY: Massively Multilingual Automatic Speech Recognition WHERE: Advanced Digital Sciences Center, Singapore WHEN: September, 2015 Speech input permits people to find data (maps, search, contacts) by talking to their cell phones. Of the 6700 languages spoken in the world, speech input is available in 40. Why so few? The problem is data. Before it can be used, speech input software must learn a language by studying hundreds of hours of transcribed audio. In most languages, finding somebody who can transcribe hundreds of hours of audio (somebody who is computer literate, yet has time available to perform this task) is nearly impossible. Faced with this problem, we proposed a radical solution: solicit transcription from people who don't speak the language. Non-native listeners make many mistakes. By building a probabilistic model of their mistakes, we are able to infer correct transcriptions, and thus to train speech technology in any language.
We are seeking a post-doctoral researcher who can scale these algorithms to commercial relevance. Necessary qualifications include a Ph.D. in speech technology, natural language processing, information theory or machine learning. Objectives of the research include the derivation, implementation, testing, and publication of new algorithms that train state of the art speech input technologies from probabilistic transcription in the under-resourced languages of southeast Asia.
This is a 20-month post-doctoral research position at the Advanced Digital Sciences Center (ADSC) in Singapore. The post-doc will work most closely with Dr. Nancy Chen, A*STAR, Singapore, and with Dr. Preethi Jyothi and Prof. Mark Hasegawa-Johnson, University of Illinois at Urbana-Champaign. For inquiries contact probtranspostdoc@gmail.com.
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6-3 | (2015-07-21) PhD position at Telecom ParisTech, France PhD position in Feature Function Learning for Sentiment Analysis in speech interactions
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6-4 | (2015-08-04) PhD offer at IRISA, Lannion, France A PhD offer (3 year, beginning in October 2015) is available in EXPRESSION team at IRISA at Lannion on Characterisation and generation of expressivity for audiobooks creation. Competences: Computer science, software development (Python, Perl, C++), machine learning.
More details: http://www.irisa.fr/fr/offres-theses/caracterisation-generation-lexpressivite-construction-livres-audio
Damien Lolive
Associate Professor
IRISA - Team Expression
University of Rennes 1
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6-5 | (2015-08-04) Post doctoral position at IRISA, Lannion, France A post-doctoral position on Pronunciation variants modelling for speech synthesis is available at ranceIRISA, Lannion. You?ll find more details on :
Position available from novembre 2015.
Salary: depending on experience
Contacts: damien.lolive@irisa.fr and gwenole.lecorve@irisa.fr
Regards, Damien Lolive
Associate Professor
IRISA - Team Expression
University of Rennes 1
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6-6 | (2015-08-15) Internship opportunity at Orange Labs
Internship opportunity at Orange Labs Incomplete requests management in human/machine dialogue. Entity: Orange Labs. Department/Team: CRM&DA/NADIA. Duration: 6 months. Contact: Hatim KHOUZAIMI (hatim.khouzaimi@orange.com) About our team: Orange Labs is the Research and Development division of Orange, the leading telecommunication company in France. The mission of the CRM&DA department (Customer Relationship Management & Data Analytics) is to invent new solutions to improve the company’s interactions with its customers by using data analysis techniques. You will be part of NADIA (Natural DIAlogue interaction), which is one of the teams composing CRM&DA and whose mission is to develop and maintain a human/machine dialogue solution, which is already widely used by customers. Your mission: Thanks to the recent improvements in the Automatic Speech Recognition (ASR) technology, research in the field of Spoken Dialogue Systems (SDSs) has been very active during the late few years. The main challenge is to design user initiative dialogue strategies where the user can use natural language to utter complex requests, with a lot of information, as opposed to system initiative ones, where the request is entered chunk by chunk. However, due to the user’s unfamiliarity with the system and the noise induced by the ASR module, the request captured by the system is often incomplete, hence rejected. The objective of this internship is to figure out solutions to detect whether a request is incomplete and not incorrect and if it is the case, to extract partial information. This will be later used by the Dialogue Manager module to ask the user to add missing information. In addition, researchers in the field of SDSs are more and more interested in improving the system’s floor management capacities. Instead of adopting a walkie-talkie approach where each of the dialogue participants has to wait for the other to release the floor before processing his utterance and coming up with a response, incremental dialogue suggests that the listener processes the speaker’s utterance on the flow, hence being able to interrupt her. In this frame, the system processes growing partial requests, which is another application of the solutions that will be studied. Incremental dialogue capacities are crucial in the development of a new generation of dialogue systems, which are more human-like, more reactive and less error-prone. Essential functions: You will improve the current dialogue solution that is developed and maintained by our team. For that, you will have to interact with researchers in the field as well as developers. According to the quality of the solutions that will be proposed, your results can be published in scientific conferences or lead to a patent. Qualifications and skills: - MSc in Computer Science or a related field. - A specialisation in Natural Language Processing is very welcome. - Object-Oriented Programming. - Good background in applied mathematics: probability and statistics. - Good English level. - Interest in Human Machine Interaction and Artificial Intelligence. - Team work. If you want to be part of an innovative experience in a team of talented people with state of art skills in the field, please submit your resume by email to hatim.khouzaimi@orange.com.
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6-7 | (2015-08-18) 1 year engineer position at INRIA Bordeaux 1 year engineer position at INRIA Bordeaux
The French National Institute of Research in Computing and Automation (INRIA, http://www.inria.fr/), research centre of Bordeaux-Sud Ouest (http://www.inria.fr/centre/bordeaux) is recruiting an engineer/developer for 12 months, in the framework of a partnership between the GEOSTAT team (http://geostat.bordeaux.inria.fr) and BATVOICE TECHNOLOGIES Company. The field of activity is the pathologic speech processing. The successful candidate will take part in the valorisation of our research and to its transposition into a cutting-edge architecture. The aim is the emergence of a new technology in a multi-support medical application. ProfileEngineer/developer or Master2 or PhD with a good knowledge of :
MissionImplementation of speech processing algorithms, based on data captured by microphone. Based on algorithms specifications, the implementations should be in the form of class modules gathered in directly executable applications. The successful candidate will be supervised by an experienced researcher and work in close collaboration with a developer/integrator from BATVOICE. The nature of developed modules will be adapted to massive data treatment, in execution and in/out in console mode only. The development will include the treatment of every exception bug. LocationJoin a team of talented researchers an engineers at the cutting-edge of science, in the stimulating environment of the French National Institute of Research in Computing and Automation (INRIA) in the famous town of Bordeaux in the south-west of France. Collaborate with a technology company close to the Parisian dynamic eco-system, and working in the MedTech area. EvolutionBy the end of this mission, the selected candidate will have the opportunity to be recruited by Batvoice Technologies. SalaryDepending on profile, between 30 K? and 45 K? per year.
Starting date From September 1, 2015 and before November 30, 2015.
Contact Dr. Khalid DAOUDI, khalid.daoudi@inria.fr
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6-8 | (2015-08-18) 1 year engineer position at INRIA Bordeaux 1 year engineer position at INRIA Bordeaux
The French National Institute of Research in Computing and Automation (INRIA, http://www.inria.fr/), research centre of Bordeaux-Sud Ouest (http://www.inria.fr/centre/bordeaux) is recruiting an engineer/developer for 12 months, in the framework of a partnership between the GEOSTAT team (http://geostat.bordeaux.inria.fr) and BATVOICE TECHNOLOGIES Company. The field of activity is the pathologic speech processing. The successful candidate will take part in the valorisation of our research and to its transposition into a cutting-edge architecture. The aim is the emergence of a new technology in a multi-support medical application. ProfileEngineer/developer or Master2 or PhD with a good knowledge of :
MissionImplementation of speech processing algorithms, based on data captured by microphone. Based on algorithms specifications, the implementations should be in the form of class modules gathered in directly executable applications. The successful candidate will be supervised by an experienced researcher and work in close collaboration with a developer/integrator from BATVOICE. The nature of developed modules will be adapted to massive data treatment, in execution and in/out in console mode only. The development will include the treatment of every exception bug. LocationJoin a team of talented researchers an engineers at the cutting-edge of science, in the stimulating environment of the French National Institute of Research in Computing and Automation (INRIA) in the famous town of Bordeaux in the south-west of France. Collaborate with a technology company close to the Parisian dynamic eco-system, and working in the MedTech area. EvolutionBy the end of this mission, the selected candidate will have the opportunity to be recruited by Batvoice Technologies. SalaryDepending on profile, between 30 K? and 45 K? per year.
Starting date From September 1, 2015 and before November 30, 2015.
Contact Dr. Khalid DAOUDI, khalid.daoudi@inria.fr
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6-9 | (2015-08-25) Postdoc / Spontaneous speech recognition and understanding, IMAG, Grenoble, France
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6-10 | (2015-08-25) Mother-tongue Pashto at Vocapia. CONTEXTE
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6-11 | (2015-08-25) Mother-tongue Somali at Vocapia CONTEXTE
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6-12 | (2015-10-06) POST-DOC OPENING IN STATISTICAL NATURAL LANGUAGE PROCESSING AT LIMSI-CNRS, FRANCE POST-DOC OPENING
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6-13 | (2015-10-16) CDD à l’Institut français de l’Éducation (IFÉ - ENS de Lyon) Offre de CDD 6 mois : Sélection d’un système automatique de phonétisation de texte, adaptation au contexte de l’apprentissage de la lecture, puis intégration au sein de la plate-forme web du projet CADOE (Calcul de l’Autonomie de Déchiffrage Offerte aux Élèves). Contexte L’Institut français de l’Éducation (IFÉ - ENS de Lyon) mène une recherche d’envergure nationale sur l’apprentissage de la lecture et de l’écriture au cours préparatoire (projet LireEcrireCP). Cette recherche réunit 60 enseignants chercheurs et doctorants répartis sur le territoire national. 131 classes ont été observées et de nombreuses données ont été recueillies et analysées. Il en ressort notamment que les textes dont moins de 31% du contenu est directement déchiffrable par les élèves pénalisent leurs apprentissages, et que ceux dont cette proportion dépasse 55% favorisent les apprentissages des élèves les plus faibles en « code » (c’est-à-dire sur les correspondances entre les lettres et les sons) à l’entrée du cours préparatoire. L’analyse nécessaire pour connaitre cette part directement déchiffrable est complexe et ne peut être réalisée au quotidien par les enseignants, mêmes chevronnés. Ils ne disposent donc pas d’une information pourtant cruciale au choix des textes à utiliser pour enseigner la lecture. Le projet CADOÉ a pour but de mettre en place une plate-forme qui permettra aux enseignants d’accéder à cette part de texte directement déchiffrable par les élèves. Pour cela, ils devront renseigner la progression de leur enseignement des correspondances entre les lettres et les sons (l’étude du « code »), indiquer quels mots ont été appris en classe, et déposer les textes « candidats » pour être utilisés comme supports de lecture. Ces textes seront automatiquement analysés et segmentés en unités graphiques. La confrontation du « code » enseigné et des mots appris en classe avec le résultat de la décomposition permettra de calculer, et de fournir en retour à l’utilisateur, la mesure de la part de texte directement déchiffrable par les élèves, autrement dit le niveau d’autonomie de déchiffrage des élèves sur le texte soumis. Compétences attendues Nous recherchons des candidats ayant, soit un profil informatique avec une spécialisation sur le traitement automatique des langues (TAL) ou le traitement automatique de la parole, soit une formation en linguistique avec spécialisation sur l’ingénierie linguistique et l’informatique. La personne recrutée étudiera des outils de phonétisation existants, et en sélectionnera un. Elle devra ensuite le configurer ou l’adapter pour que ses sorties soient conformes à la décomposition attendue proposée par Riou (2015), et assurera les tests. Elle portera le projet et sera responsable de son avancée. Elle travaillera en coordination avec l’équipe de développement Web sur les formats d’échanges entre la plate-forme et l’outil de phonétisation. Elle travaillera en étroite collaboration avec J. Riou, chargé d’étude à l’IFÉ, responsable scientifique du projet qui validera la configuration de l’outil de phonétisation et coordonnera les tests utilisateur de l’environnement développé, ainsi qu’avec P. Daubias, Ingénieur de Recherche en Informatique, responsable techniques. L’implication technique dans la réalisation de la plate-forme web CADOÉ pourra varier en fonction du profil et des compétences du(de la) candidat(e) retenu(e). L’intégration à l’équipe CADOÉ permettra. Le processus de développement sera itératif (cycle en spirale) en affinant les spécifications au vue des maquettes successives réalisées. Aspects techniques Le développement se fera pour une cible Linux et doit être performant. Le premier outil étudié (lia_phon) est écrit en C, mais son adaptation ne requiert pas nécessairement une connaissance approfondie de ce langage. D’autres outils de phonétisation sont envisageables (IrisaPhon par exemple), et les technologies ne sont pas figées. Aspects administratifs Lieu : Institut français de l'Éducation - École Normale Supérieure de Lyon Bâtiment D6 19 allée de Fontenay, 69007 Lyon Métro B : Debourg Rémunération en fonction du niveau et selon grille : de 1700 € à 2500 € brut mensuel. Début de contrat : dès que possible Merci d’envoyer votre candidature (CV + lettre de motivation) à : lire.ecrire@ens-lyon.fr Un premier examen des dossiers reçus aura lieu début novembre 2015 Durée du contrat : 6 mois
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6-14 | (2015-12-02) Master2 position at Multispeech Team, LORIA (Nancy, France) Master2 position at Multispeech Team, LORIA (Nancy, France) Automatic speech recognition: contextualisation of the language model based on neural networks by dynamic adjustment Framework of ANR project ContNomina The technologies involved in information retrieval in large audio/video databases are often based on the analysis of large, but closed, corpora, and on machine learning techniques and statistical modeling of the written and spoken language. The effectiveness of these approaches is now widely acknowledged, but they nevertheless have major flaws, particularly for what concern proper names, that are crucial for the interpretation of the content. In the context of diachronic data (data which change over time) new proper names appear constantly requiring dynamic updates of the lexicons and language models used by the speech recognition system. As a result, the ANR project ContNomina (2013-2017) focuses on the problem of proper names in automatic audio processing systems by exploiting in the most efficient way the context of the processed documents. To do this, the student will address the contextualization of the recognition module through the dynamic adjustment of the language model in order to make it more accurate. Subject Current systems for automatic speech recognition are based on statistical approaches. They require three components: an acoustic model, a lexicon and a language model. This stage will focus on the language model. The language model of our recognition system is based on a neural network learned from a large corpus of text. The problem is to re-estimate the language model parameters for a new proper name depending on its context and a small amount of adaptation data. Several tracks can be explored: adapting the language model, using a class model or studying the notion of analogy. Our team has developed a fully automatic system for speech recognition to transcribe a radio broadcast from the corresponding audio file. The student will develop a new module whose function is to integrate new proper names in the language model. Required skills Background in statistics and object-oriented programming. Localization and contacts Loria laboratory, Multispeech team, Nancy, France Irina.illina@loria.frdominique.fohr@loria.fr Candidates should email a detailed CV and diploma References [1] J. Gao, X. He, L. Deng Deep Learning for Web Search and Natural Language Processing , Microsoft slides, 2015 [2] X. Liu, Y. Wang, X. Chen, M. J. F. Gales, and P. C. Woodland. Efficient lattice rescoring using recurrent neural network langage models, in Proc. ICASSP, 2014, pp. 4941?4945. [3] M. Sundermeyer, H. Ney, and R. Schlüter. From Feedforward to Recurrent LSTM Neural Networks for Language Modeling. IEEE/ACM Transactions on Audio, Speech, and Language Processing, volume 23, number 3, pages 517-529, March 2015.
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6-15 | (2015-10-22) Scientific collaborator for the multimodal project ADNVIDEO, Marseille, France Application deadline: 12/31/2015
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6-16 | (2015-11-05) Ingénieur pour le projet LINKMEDIA de l'IRISA, Rennes, France L?e?quipe LINKMEDIA (http://www-linkmedia.irisa.fr) de l?IRISA travaille au
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6-17 | (2015-11-13) Ph.D. at Limsi, Orsay, France LIMSI (http://www.limsi.fr) seeks qualified candidates for one fully funded PhD position in the field of automatic speaker recognition. The research will be conducted in the framework of the ANR-funded project ODESSA (Online Diarization Enhanced by recent Speaker identification and Structured prediction Approaches) in partnership with EURECOM (France) and IDIAP (Switzerland).
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6-18 | (2015-11-15) 1 (W/M) researcher positions at IRCAM, Paris France
Position: 1 (W/M) researcher positions at IRCAM Starting: January 4th, 2016 Duration: 18 months Deadline for application: December, 1st, 2015
Description of the project: The goal of the ABC-DJ project (European H2020 ICT-19 project) is to develop advanced Audio Branding (recommending music for a trade-mark) technologies. For this, ABC-DJ will rely on Music Content and Semantic Analysis. Within this project, IRCAM will develop • new music content analysis algorithms (auto-tagging into genre, emotions, instrumentation, estimation of tonality and tempo) • new tools for advanced DJ-ing (audio quality measurement, segmentation into vocal parts, full hierarchical structure analysis, intelligent track summary, audio source separation).
Position description 201511ABCRES: For this project IRCAM is looking for a researcher for the development of the technologies of music content analysis and advanced DJ-ing. Required profile: • High Skill in audio signal processing (spectral analysis, audiofeature extraction, parameter estimation) (the candidate should preferably hold a PHD in this field) • High skill in machine learning (the candidate should preferably hold a PHD in this field) • High-skill in Matlab/Python programming, skills in C/C++ programming • Good knowledge of Linux, Windows, Mac-OS environments • High productivity, methodical works, excellent programming style. The hired Researchers will also collaborate with the development team and participate in the project activities (evaluation of technologies, meetings, specifications, reports).
Introduction to IRCAM: IRCAM is a leading non-profit organization associated to Centre Pompidou, dedicated to music production, R&D and education in sound and music technologies. It hosts composers, researchers and students from many countries cooperating in contemporary music production, scientific and applied research. The main topics addressed in its R&D department include acoustics, audio signal processing, computer music, interaction technologies and musicology. Ircam is located in the centre of Paris near the Centre Pompidou, at 1, Place Igor Stravinsky 75004 Paris.
Salary: According to background and experience
Applications: Please send an application letter with the reference 201511ABCRES together with your resume and any suitable information addressing the above issues preferably by email to: peeters at ircam dot fr with cc to vinet at ircam dot fr, roebel at Ircam dot fr.
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6-19 | (2015-11-13) Intership at Loria, Vandoeuvre-lès-Nancy, France Speech intelligibility: how to determine the degree of nuisance
General information
Supervisors
Irina Illina, LORIA, Campus Scientifique - BP 239, 54506 Vandoeuvre-lès-Nancy, illina@loria.fr
Patrick Chevret, INRS, 1 rue du Morvan, 54519 Vandoeuvre-lès-Nancy, patrick.chevret@inrs.fr
Motivations
The intelligibility of speech means the ability of a conversation to be understood by a listener located nearby. The level of speech intelligibility depends on several criteria: the level of ambient noise, the possible absorption of part of the sound spectrum, acoustic distortion, echoes, etc. The intelligibility of speech is used to assess the performance of telecommunication systems or absorption in rooms.
The speech intelligibility can be evaluated:
- subjectively: listeners hear several words or sentences and answer different questions (the transcription of sounds, the percentage of perceived consonants, etc.). The scores are the value of intelligibility ;
- objectively, without involving listeners, using acoustic measures: the index of speech intelligibility (speech transmission index, STI) and the interference level with speech.
Subjective measures are dependent of listeners and require a large number of listeners. This is difficult to achieve, especially when there are different types of environments. Moreover, it is necessary to evaluate this measure for each listener. Objective measures have the advantage of being automatically quantifiable and to be precise. However, which objective measures can measure the nuisance of the environment on the intelligibility of speech and people's health remains an open problem. For example, the STI index consists of measuring the energy modulation. But the energy modulation can be produced by the machines, yet it does not match the speech.
Subject
In this internship, we focus on the study of various objective measures of speech intelligibility. The goal is to find reliable measures to evaluate the level of nuisance of environment to speech understanding, to long-term mental health of people and to productivity. Some possible solutions consist to correlate the word confidence measure, noise measurement confidence and subjective measures of speech intelligibility. To develop these measures, the automatic speech recognition system will be used.
This internship will be performed through collaboration between our Multispeech team of LORIA and INRS (National Institute of Research and Safety). INRS works on professional risk identification, analysis of their impact on health and prevention. INRS has a rich corpus of recordings and subjective measures of speech intelligibility. This corpus will be used in the context of this internship. Our Multispeech team has great expertise in signal processing and has developed several methodologies for noise estimation. The Multispeech team developed the complete system of automatic speech recognition.
Required skills
Background in statistics and object-oriented programming.
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6-20 | (2015-11-15) 2 sujets de stage pour 2016 au LIA, Avignon portant sur les interactions vocales
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6-21 | (2015-11-18) PhD and Postdoctoral Opportunities in Multilingual Speech Recognition at Idiap, Martigny, Switzerland PhD and Postdoctoral Opportunities in Multilingual Speech Recognition
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6-22 | (2015-11-20) Ingénieur de recherche au LPL, Aix-en-Provence, France Le Laboratoire Parole et Langage à Aix-en-Provence propose un poste d'ingénieur de recherche à la mutation pour la campagne CNRS NOEMi d'hiver. Le détail du poste est ci-joint.
Résumé du profil : Le/la chef de projet assurera le traitement du signal (signaux acoustiques, kinématiques, physiologiques, électro-encéphalographiques, signaux vidéo), analyses statistiques des données multi-modales ; le développement de programmes pour le pré-traitement et le traitement du signal (filtrage, synthèse/resynthèse, transformations temps/fréquence, édition, extraction de paramètres, segmentation / annotation) et l'analyse statistique (ex. : modèles linéaires à effets mixtes, représentations graphiques, etc.).
Pour plus d'information, n'hésitez pas à contacter la Direction du LPL (noel.nguyen@lpl-aix.fr) ou le coordinateur du Centre d?Expérimentation sur la Parole (alain.ghio@lpl-aix.fr)
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6-23 | (2015-11-20) Postdoctoral position in speech intelligibility at IRIT Toulouse, France Title: Postdoctoral position in speech intelligibility Application deadline: 1/31/2016 Description: The decreasing mortality of Head and Neck Cancers highlights the importance to reduce the impact on Quality of Life (QoL). But, the usual tools for assessing QoL are not relevant for measuring the impact of the treatment on the main functions involved by the sequelae. Validated tools for measuring the functional outcomes of carcinologic treatment are missing, in particular for speech disorders. Some assessments are available for voice disorders in laryngeal cancer but there are based on very poor tools for oral and pharyngeal cancers involving more the articulation of speech than voice. In this context, the C2SI (Carcinologic Speech Severity Index) project proposes to develop a severity index of speech disorders describing the outcomes of therapeutic protocols completing the survival rates. There is a strong collaboration between linguists, phoneticians, speech therapists and computer science researchers, in particular those from the Toulouse Institute of Computer Science Research (IRIT), within the SAMoVA team (http://www.irit.fr/recherches/SAMOVA/). Intelligibility of speech is the usual way to quantify the severity of neurologic speech disorders. But this measure is not valid in clinical practice because of several difficulties as the familiarity effect of this kind of speech and the poor inter-judge reproducibility. Moreover, the transcription intelligibility scores do not accurately reflect listener comprehension. Therefore, our hypothesis is that an automatic assessment technic can measure the impact of the speech disorders on the communication abilities giving a severity index of speech in patients treated for head and neck and particularly for oral and pharyngeal cancer. The main objective is then to demonstrate that the C2SI, obtained by an automatic speech processing tool, produces equivalent or superior outcomes than a score of speech intelligibility obtained by human listeners, in terms of QoL foreseeing the speech handicap, after the treatment of oral and/or pharyngeal cancer. The database is actually recorded at the Institut Universitaire du Cancer in Toulouse with CVC pseudo-words, readings, short sentences focusing on prosody and spontaneous descriptions of pictures. Roadmap to develop an automatic system that will evaluate the intelligibility of impaired speech: - Study existing SAMoVA technologies and evaluate them with the C2SI protocol, - Find relevant features with the audio signal that support intelligibility, - Merge those features to obtain the C2SI, - Correlate it with the speech intelligibility scores obtained by human listeners, - Study in which way the features support understandability as well. Skills: For this project, we are looking for one candidate with a PhD degree in the areas of machine learning, signal processing, and also with: programming skills, scientific rigour, creativity, good publication record, excellent communication skills, enjoying teamwork... Salary and other conditions of employments will follow CNRS (French National Center for Scientific Research) standard rules for non-permanent researchers, according to the experience of the candidate. Location: the work will be conducted in the SAMoVA team of the IRIT, Toulouse (France). Contact: Jérôme Farinas jerome.farinas@irit.fr , Julie Mauclair julie.mauclair@irit.fr Duration: 12 to 24 months Candidates should email a letter of application, a detailed CV including a complete list of publications, and source code showcasing programming skills if available.
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6-24 | (2015-12-02) Master2 position at Multispeech Team, LORIA (Nancy, France)
Master2 position at Multispeech Team, LORIA (Nancy, France) Automatic speech recognition: contextualisation of the language model based on neural networks by dynamic adjustment Framework of ANR project ContNomina The technologies involved in information retrieval in large audio/video databases are often based on the analysis of large, but closed, corpora, and on machine learning techniques and statistical modeling of the written and spoken language. The effectiveness of these approaches is now widely acknowledged, but they nevertheless have major flaws, particularly for what concern proper names, that are crucial for the interpretation of the content. In the context of diachronic data (data which change over time) new proper names appear constantly requiring dynamic updates of the lexicons and language models used by the speech recognition system. As a result, the ANR project ContNomina (2013-2017) focuses on the problem of proper names in automatic audio processing systems by exploiting in the most efficient way the context of the processed documents. To do this, the student will address the contextualization of the recognition module through the dynamic adjustment of the language model in order to make it more accurate. Subject Current systems for automatic speech recognition are based on statistical approaches. They require three components: an acoustic model, a lexicon and a language model. This stage will focus on the language model. The language model of our recognition system is based on a neural network learned from a large corpus of text. The problem is to re-estimate the language model parameters for a new proper name depending on its context and a small amount of adaptation data. Several tracks can be explored: adapting the language model, using a class model or studying the notion of analogy. Our team has developed a fully automatic system for speech recognition to transcribe a radio broadcast from the corresponding audio file. The student will develop a new module whose function is to integrate new proper names in the language model. Required skills Background in statistics and object-oriented programming. Localization and contacts Loria laboratory, Multispeech team, Nancy, France Irina.illina@loria.frdominique.fohr@loria.fr Candidates should email a detailed CV and diploma References [1] J. Gao, X. He, L. Deng Deep Learning for Web Search and Natural Language Processing , Microsoft slides, 2015 [2] X. Liu, Y. Wang, X. Chen, M. J. F. Gales, and P. C. Woodland. Efficient lattice rescoring using recurrent neural network langage models, in Proc. ICASSP, 2014, pp. 4941?4945. [3] M. Sundermeyer, H. Ney, and R. Schlüter. From Feedforward to Recurrent LSTM Neural Networks for Language Modeling. IEEE/ACM Transactions on Audio, Speech, and Language Processing, volume 23, number 3, pages 517-529, March 2015.
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6-25 | (2015-12-03) ,PostDoc position in the field of automatic speaker recognition (ASR) at Idiap, Martigny, Switzerland The Idiap Research Institute (http://www.idiap.ch ) seeks qualified candidates for one
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6-26 | (2015-12-12) Ph.D. Position in Speech Recognition at Saarland University, Germany Ph.D. Position in Speech Recognition at Saarland University
The spoken Language Systems group from Saarland University in Germany anticipates the availability of a Ph.D. position in the area of speech recognition. This position is part of the Horizon 2020 project MALORCA, a research project on long term unsupervised adaptation of the acoustic and the language models of a speech recognition system. The research will be carried out together with a European consortium of high-profile research institutes and companies. Requirements:
Salary:
Research at Saarland University: Saarland University is one of the leading European research sites in computational linguistics and offers an active, stimulating research environment. Close working relationships are maintained between the Departments of Computational Linguistics and Computer Science. Both are part of the Cluster of Excellence, which also includes the Max Planck Institutes for Informatics (MPI-INF) and Software Systems (MPI-SWS) and the German Research Center for Artificial Intelligence (DFKI).
Each application should include: Curriculum Vitae including a list of relevant research experience in addition to a list of publications (if applies).
Applications (documents in PDF format in a single file) should be sent no later than, Sunday, January 10th to: sekretariat@LSV.Uni-Saarland.De
Further inquiries regarding the project should be directed to: Youssef.Oualil@LSV.Uni-Saarland.De or Dietrich.Klakow@LSV.Uni-Saarland.De
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6-27 | (2015-12-12) PostDoc Position in Speech Recognition at Saarland University, Germany PostDoc Position in Speech Recognition at Saarland University
The spoken Language Systems group from Saarland University in Germany anticipates the availability of a PostDoc position in the area of speech recognition. This position is part of the Horizon 2020 project MALORCA, a research project on long term unsupervised adaptation of the acoustic and the language models of a speech recognition system. The research will be carried out together with a European consortium of high-profile research institutes and companies. Requirements:
Salary:
Research at Saarland University: Saarland University is one of the leading European research sites in computational linguistics and offers an active, stimulating research environment. Close working relationships are maintained between the Departments of Computational Linguistics and Computer Science. Both are part of the Cluster of Excellence, which also includes the Max Planck Institutes for Informatics (MPI-INF) and Software Systems (MPI-SWS) and the German Research Center for Artificial Intelligence (DFKI).
Each application should include: Curriculum Vitae including a list of relevant research experience in addition to a list of publications (if applies).
Applications (documents in PDF format in a single file) should be sent no later than, Sunday, January 10th to: sekretariat@LSV.Uni-Saarland.De
Further inquiries regarding the project should be directed to: Youssef.Oualil@LSV.Uni-Saarland.De or Dietrich.Klakow@LSV.Uni-Saarland.De
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