| 6-1 | (2021-05-14) Ph D position at Prosody/Language Acquisition, Sign language: University of Lisbon
Prosody/Language Acquisition, Sign language: PhD, University of Lisbon
Applications are invited for one funded PhD position at the Phonetics and Phonology Lab and the Lisbon Baby Lab of the Center of Linguistics of the University of Lisbon (CLUL). The candidate will develop a project on the Prosody of Portuguese Sign Language/Língua Gestual Portuguesa (LGP). Research on this minority language is remarkably scarce. The work will contribute to the knowledge of the unexplored issues of production, perception and/or acquisition of prosody in LGP.
General scientific area: Linguistics, Psychology
Specific scientific area: Phonology (Prosody), Psycholinguistics, Sign language, Language processing, Language acquisition
Applications are invited from candidates holding a Master degree (MA) in Linguistics, Psychology or related areas
The work will be conducted at the Phonetics and Phonology Lab and Lisbon Baby Lab (PhonLab/LBL), under the supervison and/or co-supervision of Marina Vigário, Sónia Frota and/or Marisa Cruz. PhonLab/LBL is a leading group for research on prosody and the acquisition of prosody, with a strong interest in multimodal prosody and sign language, working with a network of partners on visual prosody, gestures and sign language. The research will take advantage of the resources, facilities and human assets available at the Lab. One of two possible PhD programs from the University of Lisbon can be chosen: PhD in Linguistics (School of Arts and Humanities, University of Lisbon) and PhD in Cognitive Sciences (University of Lisbon).
The successful candidate is expected to start in the beginning of July 2021.
Application deadline: 11th June 2021
Sónia Frota
Professora catedrática | Professor
Coordenadora Científica - CLUL | Scientific Coordinator - CLUL
Centro de Linguística da Universidade de Lisboa | Center of Linguistics of the University of Lisbon (CLUL)
https://www.researchgate.net/profile/Sonia_Frota2
Faculdade de Letras da Universidade de Lisboa | School of Arts and Humanities
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| 6-2 | (2021-05-16) Postdocs at LUDO-VIC, Paris France
Recherche de « jeunes docteurs en 1er CDI»
en linguistique, didactique des langues
ET en Natural Language Processing
La société LUDO-VIC a pour devise :
« Quels que soient votre langue maternelle et votre niveau de scolarisation, apprenez les bases de n’importe quels
concepts : une nouvelle langue, des gestes de santé/sécurité, du savoir-être, etc.. »
Ce but est atteint par la contextualisation des éléments des concepts à transmettre grâce à de courtes animations 3D
mettant en scène les avatars Ludo et Vic qui ont été spécifiquement conçus pour ne stigmatiser aucune population
sur terre et pour promouvoir l’égalité des sexes. Ces saynètes expliquent à l’oral et dans la langue maternelle de
l’apprenant les éléments à transmettre, levant ainsi la barrière de l’écrit et celle de la langue vernaculaire.
Nous avons développé ainsi une application dénommée BasicFrançais, avec un cofinancement européen, qui permet
à des populations allophones d’acquérir les bases du français, initialement au niveau A1.1, et nous nous fixons
comme but d’aller jusqu’au niveau A2.
Notre recherche de « jeunes docteurs en premier CDI » portent sur une application dérivée, nommée BasicX dans
laquelle X est une langue pratiquée sur le territoire français, allant des créoles de Mayotte, à ceux de la Réunion et de
l’arc antillais, aux langues amérindiennes de Guyane, au Kanak de Nouvelle Calédonie, au polynésien, et l’ensemble
des dialectes de la métropole (alsacien(s), basque, picard, occitan(s), etc…), mais aussi les langues parlées par les
migrants. La Direction Générale de la Langue Française et des Langues de France compte environ 75 de ces langues
dialectales, et environ 230 langues sont parlées en Europe.
Le projet de R&D consiste à créer des scénarios d’interaction dans une langue à apprendre, collecter des données et
les analyser, participer au développement des technologies de l’intelligence artificielle dans la langue en question
(reconnaissance, synthèse vocale, gestion des dialogues). Tout en étant ambitieux, ce projet relève du faisable
puisque la plage lexicale du niveau A1 ne comporte qu’environ 1000 mots et une petite centaine de dialogues très
simples.
La personne « idéale » est donc compétente en Traitement Automatique de la Parole et Intelligence Artificielle,
mais maîtrise également un dialecte parlé sur le territoire français, ou une langue issue de l’immigration. Nous
sommes conscients que ce « mouton à cinq pattes » est rare, et considèrerons donc des candidatures venant soit de
la didactique des langues, soit du NLP.
La société est basée en région parisienne, mais les candidats pourront travailler depuis leur lieu habituel de
résidence. Envoyez votre CV à jack@ludo-vic.com
LUDO-VIC SAS – 103 Boulevard Macdonald 75019 PARIS
RCS 824194492 Paris – http://www.ludo-vic.com
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| 6-3 | (2021-05-20) PhD position , LIA, Avignon, France
Main laboratory: ?Laboratoire Informatique d?Avignon? (LIA)
Start time:? September 2021
Project context
This Ph.D. position is part of the French research project DIETS (Automatic diagnosis of errors of end-to-end speech transcription systems from users perspective) funded by the ANR (French National Research Agency) which aims at analyzing finely recognition errors by taking into account their human reception, and understanding and visualizing how these errors manifest themselves in an end-to-end ASR framework. The main objectives are to propose original automatic approaches and tools to visualize, detect and measure transcription errors from the end-users perspective.
Candidate profile
?The applicant must hold a Master degree in Computer Science. ?Mastery of at least one common object programming language (Java, C++...) and one scripting language (Python, Perl...) are mandatory, furthermore experience in automatic language and speech processing, or machine learning, data mining are appreciated. He or she should also show interest in linguistics and the study of human behavior.
Objectives
The main objective of the thesis is to finely analyze transcription errors from the point of view of their reception by the user. The thesis will have three complementary parts:
1. Approaches for error detection in transcripts of end-to-end ASR systems. This should lead to original confidence measures.
2. Detailed analysis of transcription errors in French, whether human or automatic, with a traditional or end-to-end system, in order to understand how errors are viewed from a human perspective. This will shed light on new classes of errors, guided by their difficulty, or ease, to be understood by end users.
3. Realization of a new body of automatic transcriptions where errors are annotated using precise linguistic information, and information collected during perceptual tests to reflect how users perceive (and possibly correct) these errors. Carrying out different perceptual tests, by confronting humans with these transcription errors.
It will be a question of laying the first bases of a new and transversal research, at the crossroads between linguistics, computer science and cognitive sciences, for the evaluation of automatic systems and the understanding of NLP systems based on deep architectures. The Ph.D. student will then have the opportunity to learn and propose innovative approaches in automatic speech processing for the understanding of architectures with deep neural networks, but also to have an openness and skills in linguistics and on the implementation of perceptual tests.
Interests for the candidate:
- Very favorable and collaborative work environment in an internationally recognized research laboratory in language processing and machine learning.
- Implementation, analysis and proposals for innovative approaches to different ASR systems (classical and end-to-end frameworks).
- Development of complementary metrics to WER that are user-oriented.
- Transdisciplinary scientific work allowing openness to other disciplines (e.g. linguistics and cognitive sciences).
Applications? should be sent to:
and should include:
- a detailed CV (education and research experiences),
- a cover letter specifying the candidate?s research interests on this proposed Ph.D. thesis, - Bachelor (Licence) and Master grades in detail,
- at least one reference that could be contacted for recommandation.
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| 6-4 | (2021-05-25) Two fully-funded PhD positions, INRIA and Vivoka, Metz, France (updated)
Inria and Vivoka are offering two fully-funded PhD positions in the context of an
academic-industry partnership aiming to further develop the Voice Development Kit (VDK),
the very first solution allowing a company to design an embedded voice interface in a
simple, autonomous and quick way (https://vivoka.com/).
The successful candidates will share their time between Vivoka's R&D team and Inria's
Multispeech team, that is the largest research team in the field of speech processing in
France.
Detailed offers:
- Multi-factor data augmentation and transfer learning for embedded automatic speech
recognition: https://recrutement.inria.fr/public/classic/en/offres/2021-03756
- Joint embedded speech separation, diarization and recognition for the automatic
generation of meeting minutes:
https://recrutement.inria.fr/public/classic/en/offres/2021-03757
Starting date: October 1, 2021
Duration: 3 years
Location: Metz, France
Salary: from 1,870 to 1,950 EUR net/month
To apply:
Submit your application online at the above URLs and send a copy to
recrutement@vivoka.com. Applications will be assessed on a rolling basis. Please apply as
soon as possible and no later than July,16, 2021.
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| 6-5 | (2021-05-28) Position of Assistant Professor, Univ. Groningen, The Netherlands
Job description
We invite applications for an Assistant Professor in Speech Technology. Generally, for this position, you will teach and develop courses, perform research, supervise graduate research, and have an active role in shaping the emerging educational and research programme.
We recognize research as a critical part of the profile of an Assistant Professor, and therefore allocate 40% of your position to do research (provided you teach at least 2 courses/year). That research may dovetail with the courses you teach, to ensure that your expertise is integrated into the programme. Ideally, your research would overlap with that of PhD students ? and, where relevant, graduate students could contribute to your research through their thesis projects. As a team, we are keen on applying for grants in the years ahead to build consortia and further solidify our expertise.
We see teaching as an interactive and engaging process. Consequently, the courses include many individual and group activities and encourage creative, out-of-the-box, hands-on approaches to learning that balance theory and practice. Specifically, given the start-up phase of the programme and potential for growth, this position is open to a range of profiles and contributions. In addition to supervising theses within your area of expertise, you will support the teaching and/or curriculum development of courses in speech synthesis, speech recognition, Python, and machine learning for voice tech (all courses already have detailed week-by-week descriptions but lack student-ready syllabi, giving you some creative freedom -- more information about the courses, including learning outcomes, is available upon request):
? Speech Synthesis I and II
? Speech Recognition I and II
? Python for Voice Technology (and Intro to Python at the undergraduate level)
? Machine Learning for Voice Technology
If you are interested in increasing your appointment to a full-time one, you may also teach Statistics (undergraduate level) under a separate contract.
Qualifications
We are looking for an enthusiastic colleague with demonstrated teaching and research skills and an affinity for interdisciplinary approaches to teaching. Research expertise that involves speech recognition, voice synthesis, and machine learning with audio data is crucial.
The ideal candidate has:
? a PhD in Linguistics, Computer Science, AI or a comparable domain (ideally on topics related to ASR or speech synthesis)
? an ability to develop course content for the courses you will teach
? a capacity to teach master?s students and supervise master?s projects
? the willingness to apply an inter- and transdisciplinary perspective to research and education
? relevant publications
? a speech tech network in academia and/or industry
? a University Teaching Qualification, or the willingness to acquire one within two years after the starting date.
Organisation
The University of Groningen, established in 1614, is one of the oldest and most prestigious European universities. You will work at the university's newest faculty, Campus Fryslân, located in the picturesque capital of Fryslân, Leeuwarden (the European Capital of Culture in 2018). The faculty is dedicated to interdisciplinary and transdisciplinary education and research and provides a stimulating working environment in which mutual support is combined with room for individual initiative. You will become a member of our high-standing academic and international community. We challenge our staff and students to approach issues from multiple disciplines and encourage them to take a different view. We are curious about yours!
Within Campus Fryslân, you will primarily be working in the new Voice Technology Master?s programme. The MSc. Voice Technology is a one-year English language master?s programme with a highly interdisciplinary scope. It was developed in close cooperation with other universities and partners from the private sector (critical input continues to be provided by Dutch SMEs alongside international tech companies like Apple, Mozilla, and Google). This means that scientific scholarship is balanced with applied know-how in the programme. The MSc. Voice Technology is launching for the first time in September 2021 with a small cohort of students from an array of backgrounds, ranging from AI and Computer Science to Linguistics and Humanities.
Conditions of employment
We offer you in accordance with the Collective Labour Agreement for Dutch Universities:
? a salary, depending on qualifications and work experience, with a minimum of ? 3,746 to a maximum of ? 5,127 (salary scale 11) gross per month for a full-time position
? a holiday allowance of 8% gross annual income
? an 8.3% end-of-the-year allowance
? minimum of 29 holidays and additional 12 holidays in case of full-time employment.
The position has a 60-40 percent distribution with regard to teaching-research. The post will be established for a fixed term period of two years. Towards the end of that period there will be a result- and development interview in order to decide whether the appointment will be made permanent.
Application
Do you want to become a member of our team? Please send your application to us, by submitting the following documents:
1. letter of application
2. curriculum vitae
3. a statement on teaching, detailing courses taught or developed
4. email and telephone contact information of at least two referees.
You can submit your application until 13 June 11:59pm / before 14 June 2021 Dutch local time (CET) by means of the application form (click on 'Apply' below on the advertisement on the university website).
Only complete applications submitted by the deadline will be taken into consideration. The starting date for this position is 1 August 2021.
The interview will consist of two parts: the interview (30 minutes) and the mock lecture (15 minutes) during which you will demonstrate your knowledge of the research domain and showcase your teaching capabilities.
Unsolicited marketing is not appreciated.
Information
For information you can contact:
Please do not use the e-mail address(es) above for applications.
Additional information
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| 6-6 | (2021-06-02) Rand D engineer at Telepathy Labs, Zurich, Switzerland
ASR Research and Development Engineer, Speech
To strengthen our Research and Development (R&D) organization, innovate and
improve our Automatic Speech Recognition (ASR) products , we need
experienced software engineers with specific skills focused on ASR. You will be
working with the ASR research and development team, and the position will be
based in Zurich, Switzerland.
Principal responsibilities
* Work together within ASR R&D team to strengthen and extend the quality and the
functionality of the existing core engine algorithm and framework.
* Document and communicate effectively the design and implementation proposals, and
the intermediate and final development results in team internal meetings, and in wider
R&D or divisional meetings, when requested.
* Define and implement test cases and metrics processes aimed at qualifying the new
developments within the team adopted sw development and testing processes.
* Follow adopted industry standards and agile development models in place, plus be
ready to accommodate rapid customer driven specification changes.
Knowledge, Skills and Qualifications:
Years of Work Experience: 3 years of professional experience are required
Required
Skills:
The successful candidate is a team player and a fast learner with an
analytical mindset and a pragmatic approach to problem solving.
Knowledge of main ASR softwares, DSP theory, feature extraction etc.
Actual experience within ASR research and development teams.
Experience with ASR open source Toolsets such as Kaldi, Sphynx, HTK,
Fairseq, NeMo and other Pytorch / Tensorflow based libraries.
Experience with high level programming languages such as C, C++, Java.
Experience with distributed version control systems (e.g. Git).
Working knowledge of Linux Operating system.
Excellent oral and written communication skills in English.
Preferred
Skills:
Experience with LSTM and/or Attention Neural Networks and other
Deep Learning approaches as applied to ASR domain.
Knowledge of embedded software programming in C/C++.
Experience with continuous integration and delivery processes.
Experience with scripting languages such as Python, Perl, etc.
Experience in software development preferably in embedded/small
resource software system design and development.
Education: Minimum : MSc in computer science, or equivalent
Desirable : PhD degree in Computer Science, Artificial Intelligence,
Machine Learning, Speech Science.
Work Permit: Permit to work in Switzerland (EU-28 or equivalent) required.
Contact: Pierre-Edouard Honnet pe.honnet@telepathy.ai
Vijeta Avijeet vijeta.avijeet@telepathy.ai
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| 6-7 | (2021-06-03) Full professor at Radboud University, Nijmegen, The Netherlands
At Radboud University we have a position for a full professor Artificial Intelligence & Language, Speech and Communication: https://www.ru.nl/werken-bij/vacature/details-vacature/?recid=1152936&doel=embed&taal=nl
Could you include this job position on ISCA's job page:
The website mentions an ultimate date for application of 11 June, but we will be flexible for applications arriving before 16 June if sent to:Prof. José Sanders, Head of Department Language & CommunicationTel.: +31 24 361 28 02Email: jose.sanders@ru.nl
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| 6-8 | (2021-06-04)PhD and Postdoc positions at University of Bielefeld, Germany
PhD position in Phonetics (full time) at Bielefeld University, Germany
Within the newly funded Transregional Collaborative Research Center ?Constructing Explainability?, we are offering a position within the subproject on ?Technically enabled explaining of speaker traits? for a period of 4 years:
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| 6-9 | (2021-06-06) Ph D position at University of Paderborn, Germany
https://ei.uni-paderborn.de/fileadmin/elektrotechnik/fg/nth/Stellenangebote/Kennziffer4707.pdf
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| 6-10 | (2021-06-08) PhD position at University of Bielefeld, Germany
The Digital Linguistics Lab (head: JProf. Dr.-Ing. Hendrik Buschmeier) at Bielefeld University is seeking to fill a researcher position (PhD-student, E13 TV-L, 100%, fixed-term until 6/2025) in the newly established collaborative research center TRR 318 ?Constructing Explainability?[^1], sub-project A02 ?Monitoring the understanding of explanations?[^2].
Join us to work in a large interdisciplinary team (computer science, linguistics, computational linguistics, psychology, media science, economics and sociology) on research questions in the intersection of explainable AI and human-computer interaction.
Project A02 will carry out interaction studies and build statistical and computational models to monitor explainees' understanding of explanations based on their multimodal feedback (e.g., head nods, facial expressions, gaze, backchannels, clarification requests).
The formal job advertisement with information on how to apply can be found here:
https://uni-bielefeld.hr4you.org/job/view/540/research-position-for-the-sfb-trr-318-subproject-a02-hb?page_lang=en
Questions? Don?t hesitate to get in touch: hbuschme@uni-bielefeld.de
Hendrik Buschmeier
[^1]: https://www.uni-paderborn.de/en/trr318
[^2]: https://www.uni-paderborn.de/en/trr318/subprojects/a02
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| 6-11 | (2021-06-24) PhD position at IMAG, Grenoble, France
Please find below the description of a PhD position in ?Citation extraction
classification for knowledge extraction and analysis of a scientific field?.
Starting date: October 01, 2021
Deadline for Applications: July 5th, 2021
Keywords: natural language processing, citation classification, transfer
learning, deep learning
Context
The NanoBubbles ERC project objective is to understand how, when and why science
fails to correct itself. The project?s focus is nanobiology and it combines approaches
from the natural, computer science, and social sciences and the humanities (Science and
Technology Studies) to understand how error correction in science works and what
obstacles it faces. For this purpose, we aim to trace claims and corrections in various
channels of scientific communication (journals, social media, advertisements, conference
programs, etc.) via natural language processing.
The challenge is to build data sets, models and tools that enable organising and
analysing the rapidly evolving ecology of online comments complementary to conventional
scientific records:
- This means not only counting references to a document but also assessing and
leveraging the content of both cited and citing document.
- This means not only identifying named entity, claims and counter claims but
also extracting structured knowledge from text.
- This means not only taking advantage of existing data to learn models but also
building tools for creation and annotation of new sets of data so to train advance
language models.
Project objectives
Citations are an important indicator of the state of a scientific field. They
reflect how authors frame their work and influence its adoption by future researchers.
However, despite recent work in NLP [Bakhti2018,Jurgens2016,Pride2019,Yu2020], citation
behaviour and how it can be used to point out error correction lack large scale and deep
citation analyses.
The objective of this PhD is to design new NLP method to detect and qualify
citations and extract citation network in scientific research.
[Bakhti2018] Bakhti, K., Niu, Z., Yousif, A., & Nyamawe, A. S. (2018, August).
Citation function classification based on ontologies and convolutional neural networks.
In International Workshop on Learning Technology for Education in Cloud (pp. 105-115).
Springer, Cham.
[Jurgens2016] Jurgens, D., Kumar, S., Hoover, R., McFarland, D., & Jurafsky, D.
(2016). Citation classification for behavioral analysis of a scientific field. arXiv
preprint arXiv:1609.00435.
[Pride2019] Pride, D., Knoth, P., & Harag, J. (2019, June). ACT: an annotation
platform for citation typing at scale. In 2019 ACM/IEEE Joint Conference on Digital
Libraries (JCDL) (pp. 329-330). IEEE.
[Yu2020] Yu, W., Yu, M., Zhao, T., & Jiang, M. (2020, April). Identifying
referential intention with heterogeneous contexts. In Proceedings of The Web Conference
2020 (pp. 962-972).
Skills
Master 2 in Natural Language Processing, computer science or data science.
Programming experience in Python and in a deep learning framework.
Previous experience in NER, RE and dataset manipulation would be a plus.
Scientific environment
The thesis will be conducted within the Sigma and Getalp teams of the LIG laboratory
(http://sigma.imag.fr/ and https://lig-getalp.imag.fr/). The recruited person will be
welcomed within the teams which offer a stimulating, multinational and pleasant working
environment. The means to carry out the PhD will be provided both in terms of missions in
France and abroad and in terms of equipment (personal computer, access to the LIG GPU
servers).
The person will also be required to collaborate with several teams involved in the ERC
Nanobubbles project, in particular with researchers from the IRIT lab (Toulouse, France),
University of Paris Sorbonne as well as researchers from Maastricht University, Radboud
Universiteit and University of Twente based in the Netherlands.
Instructions for applying
Applications are expected until July 5th, 2021. They must contain: CV +
letter/message of motivation + master notes + letter(s) of recommendation; and be
addressed to Cyril Labbé (cyril.labbe@imag.fr), François Portet (Francois.Portet@imag.fr)
and Yasemin J. Erden (y.j.erden@utwente.nl).
Applications will be considered on the fly. It is therefore advisable to apply as
soon as possible.
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| 6-12 | (2021-06-27) PhD position at Université du Mans, France
Sujet de thèse dans le cadre d?un co-financement entre le projet Européen SELMA porté par le LIA et Le Mans Université, encadrée par Anthony Larcher, Yannick Estève et Marie Tahon.
Titre: Apprentissage actif, interprétation et contrôle pour la synthèse neuronale de parole expressive
Laboratoire d?accueil : LIUM (https://lium.univ-lemans.fr)
Site : Le Mans
Début de la thèse : septembre 2021
La thèse aura lieu au Laboratoire d?Informatique de l?Université du Mans (LIUM) dans l?équipe LST (Language and Speech Technology) et au Laboratoire d?Informatique d?Avignon (LIA). Le candidat sera basé au Mans et des séjours à Avignon seront prévus régulièrement. Le Laboratoire Informatique d?Avignon est partenaire du projet européen SELMA (https://selma-project.eu)
Profil du candidat : Le candidat devra être motivé pour travailler sur le langage écrit et parlé, et montrer un intérêt pour la synthèse de parole. Il devra avoir Master en Informatique, une expérience en machine learning sera appréciée.
L?objectif principal du projet est de proposer, développer et valider des méthodes qui permettent 1) de générer de la parole expressive à partir d?une consigne donnée par l?utilisateur soit à l?aide de systèmes text-to-speech, soit de la conversion de voix ; et 2) d?interagir avec le système au cours de l?apprentissage et lors de l?inférence pour corriger les sorties audio du système. Dans un premier temps, nous étudierons la visualisation et l?interprétation des représentations latentes apprises par un modèle neuronal état de l?art (Tacotron + WaveNet) en termes de prosodie, locuteur, expressivité et prononciation. Il faudra définir des éléments de contrôle utilisateur qui pourront prendre la forme d?annotations et seront ensuite intégrés dans le corpus d?apprentissage à l?aide de techniques tels que l?adaptation de paramètres acoustique, les embeddings, les mécanismes d?attention, ou bien l?apprentissage de modèles intermédiaires. Parallèlement, des architectures neuronales compatibles avec l?apprentissage actif (renforcement des modèles ou adaptation au domaine) seront proposés, et il faudra déterminer les stratégies les plus pertinentes pour l?apprentissage actif. Enfin, une part importante des travaux consistera à évaluer la synthèse produite, dans un contexte de livres audio ou bien de contenu journalistique.
Pour candidater : Envoyer CV + lettre de motivation avant le 10 juillet 2021 à :
anthony.larcher@univ-lemans.fr, yannick.esteve@univ-avignon.fr et marie.tahon@univ-lemans.fr
Marie Tahon Maître de Conférence / Assistant Professor Laboratoire Informatique de l?Université du Mans (LIUM)
Tél. +33 (0)2 43 83 38 44
Avenue Olivier Messiaen, 72085 - LE MANS Cedex 09 http://perso.univ-lemans.fr/~mtahon/
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| 6-13 | (2021-06-30) PhD position at Orange France
Candidater : https://orange.jobs/jobs/offer.do?joid=101323&lang=FR
Thèse - Suivi de l'état du dialogue dans un contexte dialogique long et en alignement avec les bases de connaissances - F/H
Votre rôle est d'effectuer un travail de thèse sur le sujet de recherche : Suivi de l'état du dialogue dans un contexte dialogique long et en alignement avec les bases de connaissances.
La compréhension du langage naturel est un composant fondamental des systèmes de dialogue automatiques [1,2]. Deux types de compréhension de dialogue sont identifiés: la compréhension hors contexte (un seul énoncé) et dans le contexte dialogique (plusieurs énoncés). Plusieurs solutions industrielles rendent les dialogues plus naturels grâce à la brique de compréhension hors contexte ou avec très peu de contexte (SIRI, Amazon Alexa, Cortana, Orange Djingo, RASA etc.). Les dialogues pour l'assistance technique Orange sont très complexes : ils ont en moyenne 163 tours de parole (énoncés), 2230 tokens (l'unité minimale ou morceaux de mots) en moyenne.
La compréhension du langage naturel dans un contexte dialogique long est toujours un axe de recherche ouvert [3] car il s'agit de concevoir des architectures d'apprentissage profond complexes, performantes et optimales.
La compréhension hors contexte est généralement traitée comme la projection de l'énoncé de l'utilisateur vers un modèle sémantique, au travers par exemple d'une classification de son intention et de l'extraction des valeurs des slots associés [4]. Cette représentation, contextualisée dans l'historique du dialogue, correspond à l'état de l'utilisateur tel que perçu par le système et s'appelle « Dialogue State Tracking (DST) » en anglais ou suivi de l'état du dialogue. Les approches probabilistes appellent cette brique la trace de l'état de croyance, « Belief State Tracking » ou simplement « Belief Tracking » (BT). Un challenge, (« Dialogue State Tracking » (DST) challenge) a été lancé en 2012 pour susciter le développement de nouveaux modèles de BT pour un système de dialogue vocal, prenant en compte le bruit de la reconnaissance de la parole. Depuis, des approches ont été proposées pour favoriser le transfert entre domaines pour les dialogues textuels (chatbots) et ont évolué en tirant parti des méthodes d'apprentissage automatique des Support Vector Machines [5] au Deep Learning [3,6].
Les verrous à résoudre sont :
traiter des conversations longues
traiter l'alignement avec les bases de connaissance
favoriser le transfert de domaine pour les applications multi-domaine
détecter des sujets hors domaine et traiter des nouveaux domaines
Les conversations longues restent un problème ouvert car ces approches nécessitent beaucoup de mémoire et sont gourmandes en données. On s'intéresse à l'étude de l'apprentissage sans exemples, zero-shot learning pour pouvoir développer rapidement des systèmes de dialogue sur de nouveaux domaines.
L'étude du suivi de l'état du dialogue pour les contextes longs s'inscrit naturellement dans les efforts d'investissement qu'Orange met en oeuvre dans le domaine de l'Intelligence Artificielle.
[1] Williams, Jason D et Steve Young (2007). « Partially observable Markov decision processes for spoken dialog systems ». In: Computer Speech & Language 21.2.
[2] Sarikaya, Ruhi, Geoffrey E Hinton et Anoop Deoras (2014). « Application of deep belief networks for natural language understanding ». In: IEEE/ACM.
[3] Heck, Michael et al. (juil. 2020). « TripPy: A Triple Copy Strategy for Value Independent Neural Dialog State Tracking ». SigDIAL, p. 35-44.
[4] Rojas-Barahona, Lina M. et al. (déc. 2016). « Exploiting Sentence and Context Representations in Deep Neural Models for Spoken Language Understanding ». CoLING.
[5] Henderson, Matthew, Blaise Thomson et Jason Williams (2014). « The second dialog state tracking challenge ». SIGDIAL. 263. [6] Budzianowski, Pawe? et al. (2018). « MultiWOZ - A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling ». EMNLP.
Profil :
Vous avez suivi un cursus d'ingénieur et/ou Master de Recherche, avec des connaissances dans l'apprentissage automatique et dans au moins l'un des domaines de compétences cités.
Une première expérience de mise en oeuvre d'algorithmes d'apprentissage neuronal (dans le cadre d'un stage par exemple) serait un plus.
Vous avez des compétences dans les domaines de l'Intelligence Artificielle, de l'apprentissage automatique et particulièrement dans l'apprentissage profond.
Vous disposez d'un bon niveau en mathématiques (optimisation numérique, statistiques, probabilités, etc.).
Vous maîtrisez le développement logiciel.
Vous maîtrisez l'anglais lu, écrit, parlé.
Vous êtes curieux-se, attiré-e par les nouvelles technologies, et prêt-e à suivre le rythme de leurs évolutions.
Vous aimez le travail en équipe, au sein de projets pluridisciplinaires, et contribuer à un objectif commun, tout en étant autonome sur les activités qui sont les vôtres.
Vous avez de bonnes capacités d'analyse et de synthèse.
Maîtriser un des outils d'apprentissage profond suivants : Torch, pyTorch, TensorFlow, MXNet serait un plus.
Vous aimez communiquer le résultat de vos travaux à travers de rapports écrits et des présentations orales.
Contexte
Vous rejoindrez un équipe spécialisée en dialogue, composée d'une quinzaine de personnes : chercheurs, data scientists, architectes, développeurs, thésards et stagiaires.
entité
Orange est un acteur clé de l'innovation numérique. Dans un secteur des technologies de l'information et de la communication qui connaît un bouleversement de sa chaîne de valeur, avec la multiplication des acteurs et l'apparition de nouveaux modèles économiques, l'innovation constitue un levier majeur de croissance pour Orange.
Au sein de la Division Orange Innovation dont l'ambition est de porter plus loin l'innovation d'Orange et de renforcer son leadership technologique, vous travaillerez chez DATA IA au sein de l'équipe NADIA (Natural Dialogue Interaction), qui est en charge du développement de systèmes de dialogue et qui conduit des travaux de recherche sur le dialogue en langage naturel notamment avec l'utilisation des techniques d'apprentissage (renforcement, renforcement inversé, supervisé et non supervisé).
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| 6-14 | (2021-06-12) Tenure-Track Professorship at the University of Erlangen (succession of Prof. Nöth)
Tenure-Track Professorship at the University of Erlangen (succession of Prof. Nöth);
Intelligent Speech Interfaces - Assistant Professorship with Tenure Track
https://www.fau.eu/people/careers-human-resources/professorships/#collapse_10
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| 6-15 | (2021-06-16) Ingenieur de développement INRIA Bordeaux France
Ingénieur.e développement datascience - Inria Bordeaux Sud-Ouest
Mission: Conception d’une architecture logicielle pour un outil IA en ingénierie
biomédicale (analyse et classification de voix pathologiques)
Type de contrat : CDD
Durée : 2 ans (possibilité de prolongation)
Début : à partir du 1er septembre 2021
Date limite de candidature : 31 juillet 2021
Lieu : Inria Bordeaux Sud-Ouest
Niveau de diplôme exigé : Bac + 5 ou équivalent
Autre diplôme apprécié : thèse de doctorat
Niveau d'expérience souhaité : au moins 2 ans (comme ingénieur.e ou postdoc)
Fonction : Ingénieur scientifique contractuel
Salaire brut mensuel : 2632€ à 3543€, selon diplômes et expérience professionnelle
Candidature : https://jobs.inria.fr/public/classic/fr/offres/2021-03484
Responsable : Khalid Daoudi (khalid.daoudi@inria.fr)
Contexte et atouts du poste
Inria, institut national de recherche dédié au numérique, promeut l’excellence scientifique au service du
transfert technologique et de la société.
Inria emploie 2700 collaborateurs issus des meilleures universités mondiales, qui relèvent les défis des sciences
informatiques et mathématiques. Son modèle agile lui permet d’explorer des voies originales avec ses partenaires
industriels et académiques, et de répondre aux enjeux pluridisciplinaires et applicatifs de la transition numérique.
Engagé auprès des acteurs de l’innovation, Inria crée les conditions de rencontres profitables entre recherche
publique, R&D privée et entreprises. Inria transfère vers les startup, les PME et les grands groupes ses résultats et ses
compétences, dans des domaines tels que la santé, les transports, l’énergie, la communication, la sécurité et la protection
de la vie privée, la ville intelligente, l’usine du futur... Inria développe aussi une culture entrepreneuriale ayant conduit à
la création de 120 startup.
Le centre Inria Bordeaux Sud-Ouest est un des neuf centres d’Inria et compte 20 équipes de recherche. Le
centre Inria est un acteur majeur et reconnu dans le domaine des sciences numériques. Il est au coeur d’un riche
écosystème de R&D et d’innovation : PME fortement innovantes, grands groupes industriels, pôles de compétitivité,
acteurs de la recherche et de l’enseignement supérieur.
GEOSTAT est une équipe de recherche Inria dont la thématique de recherche est le traitement de signaux
naturels complexes, notamment en biophysique (geostat.bordeaux.inria.fr).
Mission confiée
Plusieurs maladies et pathologies peuvent causer des dysfonctionnements ou des altérations dans la production
de la parole. Les plus connues sont les maladies neurodégénératives (telles que les maladies de Parkinson et
d’Alzheimer) et les maladies respiratoires (telles que l’asthme, la BPCO ou la Covid-19). On parle alors de troubles de
la parole ou de parole pathologique.
Il est maintenant établi que certaines de ces maladies se caractérisent par une manifestation précoce des
troubles de la parole. Le développement de biomarqueurs objectifs vocaux est devenu ainsi un enjeu majeur pour l’aide
au diagnostic et suivi de ces maladies. La mission de l’ingénieur(e) recruté(e) s’inscrit dans ce cadre.
L’objectif de la mission est de concevoir une architecture logicielle, en Python, pour :
1 développer une boîte à outils générique de traitement du signal dédiée à l’analyse de la parole pathologique ;
2 implémenter un biomarqueur vocal de la fonction respiratoire en utilisant des techniques d’apprentissage
statistique, dont le Deep Learning.
Cette dernière tâche s’inscrit dans le cadre d’un projet de recherche clinique en partenariat avec l’AP-HP
(Assistance Publique - Hôpitaux de Paris), notamment le service de pneumologie et de réanimation de L'hôpital La
Pitié-Salpêtrière. Le but de ce projet est le développement d’un biomarqueur vocal de l’état respiratoire et de son
évolution pour l’aide au télé-suivi de patients atteints d’une affection respiratoire, dont la Covid-19.
Principales activités
Pour des raisons de sécurité et de confidentialité, les données vocales et cliniques des patients sont hébergées
sur les serveurs EDS (Entrepôt de Données de Santé) de l’AP-HP.
La première tâche sera ainsi de développer une API permettant la communication avec l’infrastructure
d’hébergement.
La deuxième tâche sera d’implémenter des techniques éprouvées d’analyse de la parole pathologies puis
d’autres issus de recherches récentes. Cette tâche s’appuiera, le cas échéant, sur Parselmouth
(parselmouth.readthedocs.io/en/stable/) qui est une librairie Python pour Praat (www.fon.hum.uva.nl/praat/).
La troisième étape consistera à implémenter et expérimenter des techniques d’apprentissage statistique en
utilisant les données de patients. Cette tâche s’appuiera sur les framework habituels de Machine Learning (TensorFlow,
PyTorch, Scikitlearn).
Encadrement
L’ingénieur.e disposera d’un encadrement scientifique, par Khalid Daoudi de l’équipe GEOSTAT, et technique
par Dan Dutartre et François Rué du Service d'Expérimentation et de Développement (SED) d’Inria-Bordeaux.
Compétences
Être titulaire d’un diplôme d’ingénieur et/ou doctorat en sciences du numérique
Disposer d’une expérience significative dans le développement ou le pilotage d’un projet logiciel en python.
. Disposer d’une formation solide en apprentissage statistique (Machine Learning) ainsi que d’une expérience notable
dans ce domaine ;
. Disposer d’une expertise solide en développement logiciel pour être en capacité de s’adapter à différents types
langages des plus standards (Python, C, C++) ; une forte compétence en python est requise ;
. Des connaissances en traitement du signal seraient un plus très apprécié ;
. Maîtriser les concepts, la méthodologie et les outils de la qualité logicielle ;
. Maîtriser les méthodologies de gestion de projet logiciel collaboratif ;
. Maîtriser les méthodologies d’architectures logicielles modulaires ;
. Excellent relationnel ;
. Savoir travailler en équipe pluridisciplinaires ;
. Savoir s’adapter au contexte projet ;
. Être autonome dans son organisation personnelle et le reporting ;
. Avoir une bonne communication écrite et orale en français ;
. Maîtriser l’anglais technique et scientifique
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| 6-16 | (2021-07-01) Internship at Naver Labs, Grenoble, France
https://europe.naverlabs.com/job/unsupervised-speech-to-text-translation-using-adapter-modules/
Unsupervised Speech-to-Text Translation using Adapter Modules ? Internship
Description
Adapter layers have recently proven to be flexible and lightweight mechanisms for multi-lingual translation models. In this internship we plan to explore their use for speech-to-text translation as a way of leveraging mono-lingual data to be able to translate from/to new languages in an unsupervised way.
Required skills
- PhD or research master student, in NLP, speech or machine learning with an interest on language technologies
- Familiarity with modern machine learning, as applied to NLP. Evidenced by publications in the domain.
- Familiarity with deep learning frameworks and python.
References
Application instructions
Please note that applicants must be registered students at a university or other academic institution and that this establishment will need to sign an 'Internship Convention' with NAVER LABS Europe before the student is accepted.
You can apply for this position online. Don't forget to upload your CV and cover letter before you submit. Incomplete applications will not be accepted.
About NAVER LABS
NAVER LABS is a world class team of self-motivated and highly engaged researchers, engineers and interface designers collaborating together to create next generation ambient intelligence technology and services that are rich with the organic understanding they have of users, their contexts and situations.
Since 2013 LABS has led NAVER?s innovation in technology through products such as the AI-based translation app ?Papago?, the omni-tasking web browser ?Whale?, the virtual AI assistant ?WAVE?, in-vehicle information entertainment system ?AWAY? and M1, the 3D indoor mapping robot.
The team in Europe is multidisciplinary and extremely multicultural specializing in artificial intelligence, machine learning, computer vision, natural language processing, UX and ethnography. We collaborate with many partners in the European scientific community on R&D projects.
NAVER LABS Europe is located in the south east of France in Grenoble. The notoriety of Grenoble comes from its exceptional natural environment and scientific ecosystem with 21,000 jobs in public and private research. It is home to 1 of the 4 French national institutes in AI called MIAI (Multidisciplinary Innovation in Ai) It has a large student community (over 62,000 students) and is a lively and cosmopolitan place, offering a host of leisure opportunities. Grenoble is close to both the Swiss and Italian borders and is the ideal place for skiing, hiking, climbing, hang gliding and all types of mountain sports.
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| 6-17 | (2021-07-02) PhD position at LIG, Grenoble, France
Contexte:
Le projet ANR PROPICTO vise à développer un axe de recherche autour de
la communication alternative et augmentée en se focalisant sur la
transcription automatique de la parole sous forme pictographique.
PROPICTO répond à la fois à des besoins forts dans le domaine du
handicap et relève de nombreux défis de recherche autour du traitement
automatique de la langue naturelle. PROPICTO a la volonté d'être
pluridisciplinaire en coopérant avec des linguistes et le milieu du
handicap. La finalité du projet est de proposer un système qui est
capable de transcrire directement de la parole sous la forme d?une
suite de pictogrammes.
La thèse sera co-encadrée par Benjamin Lecouteux et Maximin Coavoux
Sujet:
Cette thèse a pour objectif principal de développer un module d?analyse
syntaxique automatique qui sera intégré dans la chaîne de traitement
parole->pictogrammes mise en ?uvre dans le projet PROPICTO. L?analyse
de la parole spontanée pose de nombreux problèmes pour le TAL
(disfluences, chevauchements, segmentation en phrases). Par ailleurs,
la grande majorité des travaux en analyse syntaxique automatique se
concentrent sur des jeux de données issues de textes écrits.
Dans un premier temps, nous proposons d?évaluer les méthodes
état-de-l?art en analyse syntaxique sur les treebanks de parole
existants pour le français, en particulier en utilisant des modèles de
langage préentraînés tels que FlauBERT (Le et al 2019). Dans un second
temps, nous proposons de poursuivre 2 axes de recherche :
- Analyse end-to-end : dans un contexte applicatif, une partie des
erreurs de l?analyse syntaxique sont liées à des erreurs de
reconnaissance de la parole (propagation d?erreurs). Nous proposons
(i) d?étudier si l?ajout d?informations sur le signal sonore
permettent de réduire la propogation d?erreur (ii) d?étudier la
faisabilité d?une approche end-to-end qui prédirait conjointement
la transcription du signal sonore et son analyse syntaxique.
- Analyse syntaxique incrémentale : les analyseurs état-de-l'art
actuels ne sont pas incrémentaux, ils ont besoin d'avoir accès à la
phrase entière pour commencer l'analyse (modèle de langue
préentraîné bidirectionnel). Dans le cadre applicatif « online » de
PROPICTO, il est intéressant de considérer des algorithmes
d?analyse syntaxique qui puissent commencer l?analyse au fur et à
mesure où arrive la phrase d?input, à la manière de certains
systèmes d?analyse par transition. Cela rend l?utilisation de
modèles bidirectionnels (FlauBERT) impossibles, et nécessitera de
développer des stratégies pour garantir la robustesse de
l?analyseur.
Profil recherché:
- Master ayant une forte composante Traitement Automatique des
Langues ou linguistique computationnelle
- Expérience en programmation et machine learning pour le TAL
- Bonne connaissance du français
Détails pratiques:
- Début de la thèse envisagé entre septembre et novembre 2021
- Contrat doctoral à temps plein au LIG (équipe Getalp) pour 3 ans
(salaire: min 1768e brut mensuel, plus en cas d'enseignement)
- Date limite pour postuler: 29 juin
- Pour postuler, le dossier de candidature doit comprendre: cv,
lettre de motivation, notes de master. Les candidat?es
sélectionné?es devront également transmettre leur mémoire de master
(si disponible).
Contacts (pour toutes questions ou pour postuler):
maximin.coavoux@univ-grenoble-alpes.fr et
benjamin.lecouteux@univ-grenoble-alpes.fr
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| 6-18 | (2021-07-02) PhD position at LIG Grenoble, France
encadrée par Benjamin Lecouteux, Didier Schwab et Emmanuelle Esperança-Rodier
Traduction automatique de la parole vers des pictogrammes.
PROPICTO vise à développer un axe de recherche autour de la communication alternative et augmentée en se focalisant sur la transcription automatique de la parole sous forme pictographique. PROPICTO répond à la fois à des besoins forts dans le domaine du handicap et relève de nombreux défis de recherche autour du traitement automatique de la langue naturelle. PROPICTO a la volonté d?être pluridisciplinaire en coopérant avec des linguistes et le milieu du handicap. La finalité du projet est de proposer un système qui est capable de transcrire directement de la parole sous la forme d?une suite de pictogrammes.
Cette thèse sera axée sur la traduction de l?oral vers des ensembles de pictogrammes.
L?un des verrous scientifique de cette thèse est de chercher à pallier la quantité limitée d?exemples sous forme de pictogrammes et de corpus parole/pictogrammes.
Les approches utilisées s?inspireront dans un premier temps des approches de la traduction de la parole massivement multilingue où d?autres langues peuvent aider à traduire une langue pour laquelle les données sont rares.
Les aspects simplification de la langue seront également abordées dans ce sujet et appuyées par une autre thèse portant sur l?analyse syntaxique de l?oral.
Parallèlement au déroulement de cette thèse, des récoltes de corpus au sein de différentes institutions seront réalisées pour obtenir des paires parole/pictogrammes et répondre aux attentes en situation réelle.
L?évaluation des méthodes sera également une dimension importante de cette thèse et pourra s?inspirer, par exemple, des méthodes d?évaluation de la traduction automatique.
Profil recherché:
- Solide expérience en programmation & machine learning pour le TAL, notamment l?apprentissage profond
- Master ayant une composante Traitement Automatique des Langues ou linguistique computationnelle
- Bonne connaissance du français
Détails pratiques:
- Début de la thèse entre septembre et novembre 2021
- Contrat doctoral à temps plein au LIG (équipe Getalp) pour 3 ans (salaire: min 1768?e brut mensuel)
Environnement scientifique/
La thèse sera menée au sein de l'équipe Getalp du laboratoire LIG (https://lig-getalp.imag.fr/). La personne recrutée sera accueillie au sein de l?équipe qui offre un cadre de travail stimulant, multinational et agréable.
Les moyens pour mener à bien le doctorat seront assurés tant en ce qui concerne les missions en France et à l?étranger qu?en ce qui concerne le matériel (ordinateur personnel, accès aux serveurs GPU du LIG, Grille de calcul Jean Zay du CNRS).
/Comment postuler ?/
Les candidats doivent être titulaires d'un Master en informatique ou en traitement automatique du langage naturel (ou être sur le point d'en obtenir un). Ils doivent avoir une bonne connaissance des méthodes d?apprentissage automatique et idéalement une expérience en collecte et gestion de corpus. Ils doivent également avoir une bonne connaissance de la langue française. Une expérience dans le domaine du traitement automatique de la parole ou de la traduction automatique (neuronaux ou pas ) et/ou une sensibilisation au milieu du handicap serait un plus.
Références :
LeBenchmark: A Reproducible Framework for Assessing Self-Supervised Representation Learning from Speech Solene Evain, Ha Nguyen, Hang Le, Marcely Zanon Boito, Salima Mdhaffar, Sina Alisamir, Ziyi Tong, Natalia Tomashenko, Marco Dinarelli, Titouan Parcollet, Alexandre Allauzen, Yannick Esteve, Benjamin Lecouteux, Francois Portet, Solange Rossato, Fabien Ringeval, Didier Schwab, Laurent Besacier
Hang Le, Loïc Vial, Jibril Frej, Vincent Segonne, Maximin Coavoux, et al.. FlauBERT: Unsupervised Language Model Pre-training for French. LREC, 2020, Marseille, France. ?hal-02890258?
Hang Le, Juan Pino, Changhan Wang, Jiatao Gu, Didier Schwab, et al.. Dual-decoder Transformer for Joint Automatic Speech Recognition and Multilingual Speech Translation. COLING 2020 (long paper), Dec 2020, Virtual, Spain. ?hal-02991564?
Didier Schwab, Pauline Trial, Céline Vaschalde, Loïc Vial, Benjamin Lecouteux. Apporter des connaissances sémantiques à un jeu de pictogrammes destiné à des personnes en situation de handicap : Un ensemble de liens entre Wordnet et Arasaac, Arasaac-WN. TALN 2019, 2019, Toulouse, France. ?hal-02127258?
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| 6-19 | (2021-07-04) Post-doctoral research position - L3i - La Rochelle France
-- Post-doctoral research position - L3i - La Rochelle France
---------------------------------------------------------------------------------------------------------------------------
Title : Emotion detection by semantic analysis of the text in comics speech balloons
The L3i laboratory has one open post-doc position in computer science, in the specific field of natural language processing in the context of digitised documents.
Duration: 12 months (an extension of 12 months will be possible)
Position available from: As soon as possible, 2021
Salary: approximately 2100 ? / month (net)
Place: L3i lab, University of La Rochelle, France
Specialty: Computer Science/ Document Analysis/ Natural Language Processing
Contact: Jean-Christophe BURIE (jcburie [at] univ-lr.fr) / Antoine Doucet (antoine.doucet [at] univ-lr.fr)
Position Description
The L3i is a research lab of the University of La Rochelle. La Rochelle is a city in the south west of France on the Atlantic coast and is one of the most attractive and dynamic cities in France. The L3i works since several years on document analysis and has developed a well-known expertise in ?Bande dessinée?, manga and comics analysis, indexing and understanding.
The work done by the post-doc will take part in the context of SAiL (Sequential Art Image Laboratory) a joint laboratory involving L3i and a private company. The objective is to create innovative tools to index and interact with digitised comics. The work will be done in a team of 10 researchers and engineers.
The team has developed different methods to extract and recognise the text of the speech balloons. The specific task of the recruited researcher will be to use Natural Language Processing strategies to analyse the text in order to identify emotions expressed by a character (reacting to the utterance of another speaking character) or caused by it (talking to another character). The datasets will be collections of comics in French and English.
Qualifications
Candidates must have a completed PhD and a research experience in natural language processing. Some knowledge and experience in deep learning is also recommended.
General Qualifications
? Good programming skills mastering at least one programming language like Python, Java, C/C++
? Good teamwork skills
? Good writing skills and proficiency in written and spoken English or French
Applications
Candidates should send a CV and a motivation letter to jcburie [at] univ-lr.fr and antoine.doucet [at] univ-lr.fr.
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| 6-20 | (2011-07-13) PhD Position at CNRS
Modelisation of gestures and speech during interactions
Application Deadline : 23 August 2021
Ensure that your candidate profile is correct before applying. Your profile information will be added to the details for each application. In order to increase your visibility on our Careers Portal and allow employers to see your candidate profile, you can upload your CV to our CV library in one click!
General information
Reference : UMR5267-FABHIR-001
Workplace : MONTPELLIER
Date of publication : Monday, July 12, 2021
Scientific Responsible name : Slim Ouni
Type of Contract : PhD Student contract / Thesis offer
Contract Period : 36 months
Start date of the thesis : 1 October 2021
Proportion of work : Full time
Remuneration : 2 135,00 € gross monthly
Description of the thesis topic
One of the main objectives of social robotics research is to design and develop robots that can engage in social environments in a way that is appealing and familiar to humans. However, interaction is often difficult because users do not understand the robot's internal states, intentions, actions, and expectations. Thus, to facilitate successful interaction, social robots should provide communicative functionality that is both natural and intuitive. Given the design of humanoid robots, they are typically expected to exhibit human-like communicative behaviors, using speech and non-verbal expressions just as humans do. Gestures help in conveying information which speech alone cannot provide and need to be completed, as in referential, spatial or iconic information [HAB11]. Moreover, providing multiple modalities helps to dissolve ambiguity typical of unimodal communication and, as a consequence, to increase robustness of communication. In multimodal communication, gestures can make interaction with robots more effective. In fact, gestures and speech interact. They are linked in language production and perception, with their interaction contributing to an effective communication [WMK14]. In oral-based communication, human listeners have been shown to be well attentive to information conveyed via such non-verbal behaviors to better understand the acoustic message [GM99].
This topic can be addressed in the field of robotics where few approaches incorporate both speech and gesture analysis and synthesis [GBK06, SL03], but also in the field of developing virtual conversational agents (talking avatars), where the challenge of generating speech and co-verbal gesture has already been tackled in various ways [NBM09, KW04, KBW08].
For virtual agents, most existing systems simplify the gesture-augmented communication by using lexicons of words and present the non-verbal behaviors in the form of pre-produced gestures [NBM09]. For humanoid robots the existing models of gesture synthesis mainly focus on the technical aspects of generating robotic motion that fulfills some communicative function, but they do not combine generated gestures with speech or just pre-recorded gestures that are not generated on-line but simply replayed during human-robot interaction.
Missions
The goal of this thesis is to develop a gesture model for a credible communicative robot behavior during speech. The generation of gestures will be studied when the robot is a speaker and when it is a listener. In the context of this thesis, the robot will be replaced by an embodied virtual agent. This allows applying of the outcome of this work in both virtual and real world. It is possible to test the results of this work on a real robot by transferring the virtual agent behavior to the robot, when possible, but it is not an end in itself.
In this thesis, two main topics will be addressed: (1) the prediction of communication-related gesture realization and timing from speech, and (2) the generation of the appropriate gestures during speech synthesis. When the virtual agent is listening to a human interlocutor, the head movement is an important communicative gesture that may give the impression that the virtual agent understands what is said to it and that may make the interaction with the agent more effective. One challenge is to extract from speech, both acoustic and linguistic cues [KA04], to characterize the pronounced utterance and to predict the right gesture to generate (head posture, facial expressions and eye gaze [KCD14]). Synchronizing the gestures with the interlocutor speech is critical. In fact, any desynchronization may induce an ambiguity in the understanding of the reaction of the virtual agent. The gesture timing correlated with speech will be studied. In this work, generating the appropriate gesture during speech synthesis, mainly head posture, facial expressions and eye gaze, will be addressed.
To achieve these goals, motion capture data during uttered speech will be acquired synchronously with the acoustic signal. Different contexts will be considered to achieve the collection of sufficiently rich data. This data will be used to identify suitable features to be integrated within the framework of machine learning techniques. As the data is multimodal (acoustic, visual, gestures), each component will be used efficiently in collecting complementary data. The speech signal will be used in the context of a speech-recognition system to extract the linguistic information, and acoustic features helps to extract non linguistic information, as F0 for instance. The correlation between gestures and speech signal will also be studied. The aim of the different analyses is to contribute to the understanding of the mechanism of oral communication combined with gestures and to develop a model that can predict the generation of gestures in the contexts of speaking and listening.
References
[GBK06] Gorostiza J, Barber R, Khamis A, Malfaz M, Pacheco R, Rivas R, Corrales A, Delgado E, Salichs M (2006) Multimodal human-robot interaction framework for a personal robot. In: RO-MAN 06: Proc of the 15th IEEE international symposium on robot and human interactive communication
[GM99] Goldin-Meadow S (1999) The role of gesture in communication and thinking. Trends Cogn Sci 3:419–429
[HAB11] Hostetter AB (2011) When do gestures communicate? A meta- analysis. Psychol Bull 137(2):297–315
[NBM09] Niewiadomski R, Bevacqua E, Mancini M, Pelachaud C (2009) Greta: an interactive expressive ECA system. In: Proceedings of 8th int conf on autonomous agents and multiagent systems (AA- MAS2009), pp 1399–1400
[KA04] Kendon, Adam, 2004. Gesture – Visible Action as Utterance. Cambridge University Press.
[KBW08] Kopp S, Bergmann K, Wachsmuth I (2008) Multimodal commu- nication from multimodal thinking—towards an integrated model of speech and gesture production. Semant Comput 2(1):115–136
[KCD14] Kim, Jeesun, Cvejic, Erin, Davis, Christopher, Tracking eyebrows and head gestures associated with spoken prosody. Speech Communication (57), 2014.
[KW04] Kopp S, Wachsmuth I (2004) Synthesizing multimodal utter- ances for conversational agents. Comput Animat Virtual Worlds 15(1):39–52
[SL03] Sidner C, Lee C, Lesh N (2003) The role of dialog in human robot interaction. In: International workshop on language understanding and agents for real world interaction
[WMK14] Petra Wagner, Zofia Malisz, Stefan Kopp, Gesture and speech in interaction: An overview, Speech Communication, Volume 57, 2014, Pages 209-232.
Work Context
Funded by the MITI (CNRS), the project GEPACI (for gestures and speech in interactionnal contexts) is led by the UMR5267 Praxiling and UMR7503 LORIA laboratories. Consequently, the successfull candidate will work at the LORIA Nancy. Furthermore, work stays at Montpellier will be organized.
Constraints and risks
No specific risk.
Additional Information
Financement PRIME80 MITI.
We talk about it on Twitter!
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| 6-21 | (2021-07-16) Ingénieur d’étude en informatique mobile, Université Grenoble Alpes, France
Appel à candidatures
Ingénieur d’étude en informatique mobile
Université Grenoble Alpes
Le Laboratoire d’Informatique de Grenoble (LIG) recrute une personne motivée et force de
proposition pour un contrat d’ingénieur d’étude de 12 mois (renouvelable une fois) en
informatique mobile. La personne recrutée contribuera au projet THERADIA -
https://www.theradia.fr/, qui consiste à développer un assistant virtuel pour accompagner
des patients souffrant de troubles cognitifs lors de la réalisation de séances de remédiation
cognitive à domicile.
Collecte de données d’interaction avec l’agent Theradia piloté par un humain (magicien d’Oz).
Sujet : Développement d’un système mobile pour la collecte, la gestion et l’annotation de
données d’interactions humaines
Le travail consiste à poursuivre le développement d’un logiciel d’annotation en ligne de
données audiovisuelles d’interactions humaines, afin d’y incorporer un certain nombre de
fonctionnalités souhaitées ; e.g., acquisition audiovisuelle des annotateurs, minutage et
contrôle automatique des annotations, interface graphique dynamique, etc. Ce travail sera
réalisé en collaboration avec l’entreprise qui a conçu cet outil (ViaDialog - Paris), ainsi que
l’équipe EMC de l’Université de Lyon 2.
L’outil d’annotation sera ensuite exploité par une population d’annotateurs qu’il faudra
recruter, former à l’outil à l’aide de tutoriaux, et suivre pendant l’annotation des données,
notamment au moyen de scripts permettant de contrôler automatiquement certains aspects
critiques de l’annotation.
Les collaborateurs du projet exploiteront ces annotations pour automatiser les différentes
composantes technologiques constituant l’assistant virtuel, système qui est joué pour l’instant
par un humain pilotant (magicien d’Oz) une application distribuée sur deux machines. Le
système, une fois automatisé, sera déployé sur une plateforme mobile dont il faudra assurer
l’intégration et le bon fonctionnement, notamment pour la collecte continue et parallèle de
données d’interaction multimodales auprès des utilisateurs de l’application, et ce en parfait
respect de la RGPD.
Enfin, une dernière tâche consiste en la valorisation des travaux réalisés auprès de la
communauté scientifique, en participant notamment à l’écriture d’articles scientifiques
présentant les travaux réalisés, et en développant une interface web permettant de faciliter
l’accès aux données collectées et la gestion des licences utilisateurs soumises via l’interface.
Début de contrat : dès que possible
Durée de contrat : 12 mois (renouvelable une fois)
Salaire : selon l’expérience (jusqu’à 3444€ brut / mois)
Environnement scientifique :
La personne recrutée sera accueillie au sein du Groupe d’Étude en Traitement Automatique
des Langues et de la Parole (GETALP) du LIG, qui offre un cadre dynamique, multinational et
stimulant pour conduire des activités de recherche pluridisciplinaire de haut niveau. Les
moyens pour mener à bien les travaux seront assurés tant en ce qui concerne les missions en
France et à l’étranger qu’en ce qui concerne le matériel (ordinateur personnel, accès aux
serveurs du LIG).
Profil de la personne recherchée :
Nous cherchons une personne ayant un diplôme de Master ou d’Ingénieur en informatique
mobile, avec d’excellentes compétences en programmation web (java, python), exécution de
framework web (Angular 10, Flask/fastApi), et en bases de données(SQL). Cette personne doit
avoir une curiosité naturelle pour les sciences, pouvoir travailler de façon autonome, être pro-
active et rendre compte de l’avancement des travaux de façon régulière, être force de
proposition en cas de problème à résoudre, et surtout aimer travailler en collaboration avec
des partenaires diversifiés (industrie / académie). Une participation à l’écriture d’articles
scientifiques est également attendue.
Comment postuler ?
Les candidatures sont attendues au fil de l’eau et le poste sera ouvert jusqu’à ce qu’il soit
pourvu. Elles doivent être adressées à Fabien Ringeval (Fabien.Ringeval@imag.fr) et François
Portet à (Francois.Portet@imag.fr). Le dossier de candidature doit contenir :
- Curriculum vitae détaillé montrant les compétences attendues pour le poste
- Lettre de motivation exprimant votre intérêt et l’adéquation de votre profil
- Informations de contact et lettre de recommandation de deux personnes référentes
- Au moins deux exemples de réalisation démontrant vos compétences techniques
- Diplôme de Master ou d’Ingénieur
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| 6-22 | (2021-07-30) 5 PhD fellowships in Machine Learning and Information Retrieval , University of Copenhagen
**** 5 PhD fellowships in Machine Learning and Information Retrieval ****
**** Department of Computer Science, University of Copenhagen ****
The Machine Learning Section of the Department of Computer Science at the Faculty of Science at the University of Copenhagen (DIKU) is offering five fully-funded PhD Fellowships in Machine Learning and Information Retrieval, commencing 1 January 2022 or as soon as possible thereafter.
- Deadline to apply: August 15, 2021
* Our group and research, and what do we offer:
--------------------------
The fellows will join the Machine Learning Section at DIKU. The Machine Learning section is among the leading research environments in Artificial Intelligence and Web & Information Retrieval in Europe (in the top 5 for 2020, according to csrankings.org), with a strong presence at top-tier conferences, continuous collaboration in international & national research networks, and solid synergies with big tech, small tech, and industry. The Machine Learning section consists of a vibrant selection of approximately 65 talented researchers (40 of whom are PhD and postdoctoral fellows) from around the world with a diverse set of backgrounds and a common incessant scientific curiosity and openness to innovation.
* The fellows will conduct research, having as starting point the following broad research areas:
--------------------------
- a fully-funded PhD in machine learning evaluation;
- a fully-funded PhD in bias and interpretability for machine learning;
- a fully-funded PhD in overparameterization and generalizability in deep neural architectures;
- a fully-funded PhD in applied machine learning and/or information retrieval with focus on human-centered computing aspects;
- a fully-funded PhD in web & information retrieval.
* Who are we looking for?
--------------------------
We are looking for candidates with a MSc degree in a subject relevant for the research area. The successful candidate is expected to have strong grades in Machine Learning and/or Information Retrieval. For one of the PhDs, the candidate is expected to also have strong grades in Human-Centered Computing. The candidate should have a preliminary research record as witnessed by a master thesis or publications in the area.
???
Maria Maistro, PhD
Tenure-track Assistant Professor
Department of Computer Science
University of Copenhagen
Universitetsparken 5, 2100 Copenhagen, Denmark
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| 6-23 | (2021-08-04) Several Open Positions at KUIS AI Center, Koc University, Istanbul, Turkey
Several Open Positions at KUIS AI Center
Koc University, Istanbul, Turkey
https://ai.ku.edu.tr/
Koç University & ?? Bank Artificial Intelligence Center (KUIS AI) was established in March 2020 with a generous donation from ?? Bank. With its 15 core and 20 affiliated faculty members from engineering, medicine, science and other fields, and over 100 graduate students and research staff, it targets to be a leading research institution in artificial intelligence research, education, and industrial collaboration. Research areas in the center are computer vision, computational biology and medicine, human-computer interaction, machine learning, multimedia signal processing, natural language processing, robotics, and systems and AI. Located in Istanbul, Turkey, Koç University is a non-profit, research-intensive, selective admissions university that provides a world-class education in English. It offers top-quality undergraduate and graduate programs in Engineering, Social Sciences, Humanities, Business and Medicine to the best students from Turkey and abroad. Koç University has been ranked 1st in Turkey by the Times Higher Education World University Rankings 2021 and the QS World University Rankings 2021 and is among the top 250 universities worldwide for Engineering (THE Subject Rankings 2021).
There are currently several open positions at KUIS AI, which are listed below:
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Research Faculty Positions (2 positions)
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Responsibilities: Conducting independent research, advising graduate students, collaborating with the AI faculty members, supporting industrial projects, acquiring research funding, publishing research articles in high impact journals/conferences
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Eligibility: PhD degree from a reputable university, research experience in AI/ML/DL, strong publication record, post-doctoral research experience
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Key position benefits
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1-year contract with possibility of 2-years extension
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Starting salary is 15K TL/month (net): can be higher depending on the qualifications of the candidate
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Financial and logistic support for accommodation within defined limits
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Monthly meal card covering 2 meals per day in the cafeteria
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Health insurance coverage for the researcher
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Full travel support for attending top-tier conferences
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A high-end laptop computer, access to our state of the art GPU cluster, and additional cloud support as needed.
How to apply: send your CV, Research Statement, and names of two references to ai-admissions@ku.edu.tr. For enquiries please contact ai-admissions@ku.edu.tr.
2)Open Post-Doc Positions (3 positions)
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Responsibilities: Working on a specific research project under the supervision of an AI faculty member, supervising day-to-day activities of graduate students, acquiring research funding, publishing research articles in high impact journals/conferences
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Position Details: we seek fellows in the research areas of computer vision, computational biology and medicine, human-computer interaction, machine learning, multimedia signal processing, natural language processing, robotics, and systems and AI.
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Eligibility: PhD degree from a reputable university, research experience in AI/ML/DL, strong publication record
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Key position benefits
-
1-year contract with the possibility of a 1-year extension
-
Starting salary is 10K TL/month (net): can be higher depending on the qualifications of the candidate
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Financial and logistic support for accommodation within defined limits
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Monthly meal card covering 2 meals per day in the cafeteria
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Health insurance coverage for the researcher
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Full travel support for attending top-tier conferences
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A high-end laptop computer, access to our state of the art GPU cluster, and additional cloud support as needed.
How to apply: send your CV, Research Statement, and names of two references to ai-admissions@ku.edu.tr. For enquiries please contact the individual faculty member of your interest (https://ai.ku.edu.tr/positions/)
3)Open Research Engineer Positions (2 positions)
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Responsibilities: Working under the supervision of AI faculty members to support industrial/academic projects in data science and AI, provide technical and software development support for the computational infrastructure of AI Center, good personal skills: the ability to work in industrial projects and interact with the industrial partners to understand their needs
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Eligibility: B.S/M.S. degree from a reputable university, strong computational skills in AI/ML/DL
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Key position benefits
-
1-year contract with possibility of 2-years extension
-
Starting salary is 10K TL/month (net), but may be higher depending on the qualifications of the candidate
-
Opportunity for applied research with industry partners
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Financial and logistic support for accommodation within defined limits
-
Monthly meal card covering 2 meals per day in the cafeteria
-
Health insurance coverage for the researcher
-
A high-end laptop computer, access to our state of the art GPU cluster, and additional cloud support as needed.
How to apply: send your CV and the names of two references to ai-admissions@ku.edu.tr. For enquiries please contact ai-admissions@ku.edu.tr.
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| 6-24 | (2021-08-20) JUNIOR PROFESSOR IN NATURAL LANGUAGE PROCESSING AND MULTIMEDIA INTERACTION , Katholieke Universiteit Leuven, Belgium
JUNIOR PROFESSOR IN NATURAL LANGUAGE PROCESSING AND MULTIMEDIA INTERACTION
In the Science, Engineering and Technology Group of KU Leuven (Belgium), Faculty of Engineering Science, Department of Computer Science, there is a full-time tenure-track academic vacancy in the area of natural language processing and multimedia interaction. We seek applications from internationally oriented candidates with an outstanding research track record and excellent didactic skills. The successful candidate will perform research in the Human-Computer Interaction research unit. He or she holds a PhD in Computer Science (or a relevant equivalent degree) with focus on natural language processing and multimedia interaction, and has excellent knowledge of the fundamental principles, algorithms and methods of machine learning.
The tenure track of a junior professor lasts 5 years. After this period and subject to a positive evaluation of the tenure track, he or she will be permanently appointed as an associate professor.
More info on the vacancy and instructions on how to apply see: https://www.kuleuven.be/personeel/jobsite/jobs/60022759?hl=en&lang=en
You can apply for this professorship till October 15, 2021.
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| 6-25 | (2021-08-24) Assistant/Associate Professor position in Machine Learning (tenure) at Telecom Paris France
Telecom Paris, a founding member of Institut Polytechnique de Paris, a member of Institut Mines-Telecom (IMT), and one of the top French Engineering schools is opening an Assistant/Associate Professor position in Machine Learning (tenure).
The position is within the Machine Learning, Statistics & Signal Processing research group (S2A) and is open to a wide variety of research topics around the team expertise, which covers both theoretical and methodological works in Machine Learning, at the interface of computational/mathematical statistics, stochastic modelling, time-series analysis, signal processing and optimization.Though, expertise in one of the following subjects is at least desired:
- trustworthy machine learning (reliable, robust, fair, explainable)
- online learning, reinforcement learning
- structured prediction / multi-task
- large scale learning, frugal learning
- time-series, spatio-temporal data
More information is given at :
Additional informationIn the context of the Institut Polytechnique de Paris, the activities in Data Science and AI of the S2A team benefit from the center Hi!Paris (https://www.hi-paris.fr), offering seminars, workshops and fundings through calls for project The position? Permanent position? 19 place Marguerite Perey - 91120 Palaiseau - FranceApplicationApplication must be performed through one of the websites(French) : https://institutminestelecom.recruitee.com/o/maitre-de-conferences-en-apprentissage-statistique-fh-a-telecom-paris-cdi(English) : https://institutminestelecom.recruitee.com/l/en/o/maitre-de-conferences-en-apprentissage-statistique-fh-a-telecom-paris-cdiImportant dates? September 24, 2021 : application deadline? October 25-26 and November 4-5: interviews (by visio-conference eventually)Winter 2021/22: beginningContact :Stephan Clémençon (Head of the S2A group)stephan.clemencon@telecom-paris.frFlorence d?Alché (Holder of the Chair DSAIDIS)florence.dalche@telecom-paris.frFor more info on being an Associate Professor at Telecom Paris, contact rh@telecom-paris.frOther web Sites :Image, Data, Signal Department: web link LTCI lab: web linkS2A team: web link Télécom Paris: web link
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| 6-26 | (2021-08-28) JUNIOR PROFESSOR IN NATURAL LANGUAGE PROCESSING AND MULTIMEDIA INTERACTION at KULeuven, Belgium
JUNIOR PROFESSOR IN NATURAL LANGUAGE PROCESSING AND MULTIMEDIA INTERACTION
In the Science, Engineering and Technology Group of KU Leuven (Belgium), Faculty of Engineering Science, Department of Computer Science, there is a full-time tenure-track academic vacancy in the area of natural language processing and multimedia interaction. We seek applications from internationally oriented candidates with an outstanding research track record and excellent didactic skills. The successful candidate will perform research in the Human-Computer Interaction research unit. He or she holds a PhD in Computer Science (or a relevant equivalent degree) with focus on natural language processing and multimedia interaction, and has excellent knowledge of the fundamental principles, algorithms and methods of machine learning.
The tenure track of a junior professor lasts 5 years. After this period and subject to a positive evaluation of the tenure track, he or she will be permanently appointed as an associate professor.
More info on the vacancy and instructions on how to apply see: https://www.kuleuven.be/personeel/jobsite/jobs/60022759?hl=en&lang=en
You can apply for this professorship till October 15, 2021.
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| 6-27 | (2021-08-24) Research Associate at the University of Edinburgh , UK
A 5-year fixed-term post for a Research Associate at the University of Edinburgh who will work within an international team to design, implement, and test computational implementations of models of speech articulation planning. The post-holder will contribute to a European Research Council-funded project ?Planning the Articulation of Spoken Utterances? (PI: Alice Turk). The project?s goal is to understand the representations and processes involved in planning speech articulation. The post-holder should have excellent programming skills and an interest in speech articulation or non-speech motor control. More information and instructions for how to apply can be found here: https://elxw.fa.em3.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/job/1884/?utm_medium=jobshare
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| 6-28 | (2021-09-06) Postdoc positions in affective computing, Grenoble Alps University, France
Call for postdoc applications in affective computing (Grenoble Alps University) Summary The Grenoble Alps University has an open position for a highly motivated postdoc researcher. The successful candidate will be working on the multi-disciplinary research project THERADIA, which aims at creating an adaptative virtual assistant that accompanies patients suffering from cognitive disorders during the completion of cognitive remediation exercises at home. The person recruited will have the exciting opportunity to develop new machine learning techniques for the robust detection of affective behaviours from audiovisual data collected in-the-wild. Models will be embodied in the virtual agent to monitor and adapt the interaction with the patient, and the whole system will be further tested in a clinical trial to demonstrate the effectiveness of the agent for accompanying patients suffering from cognitive conditions during digital therapies.
Duration: 2 years,
Salary: according to experience (up to 4142€ / month)
Scientific environment The person recruited will be hosted within the GETALP team of the Laboratoire d’Informatique de Grenoble (LIG), which offers a dynamic, international, and stimulating framework for conducting high-level multi-disciplinary research.
The GETALP team is housed in a modern building (IMAG) located on a 175-hectare landscaped campus that was ranked as the eighth most beautiful campus in Europe by Times Higher Education magazine in 2018.
Requirements The ideal candidate must have a PhD degree and a strong background in machine learning, and affective computing or cognitive science/neuroscience. The successful candidate should have:
• Good knowledge of machine learning techniques
• Good knowledge of speech and image processing
• Good knowledge of experimental design and statistics
• Strong programming skills in Python
• Excellent publication record
• Willing to work in multi-disciplinary and international teams
• Good communication skills
Application: Applications are expected to be received on an ongoing basis and the position will be open until filled. Applications should be sent to Fabien Ringeval (fabien.ringeval@imag.fr) and François Portet (francois.portet@imag.fr). The application file should contain:
• Curriculum vitae
• Recommendation letter
• One-page summary of research background and interests
• At least three publications demonstrating expertise in the aforementioned areas
• Pre-defence reports and defence minutes; or summary of the thesis with date of defence for those currently in doctoral studies
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| 6-29 | (2021-09-09) 2 PhD positions at UNIv. Delft, The Netherlands
Job description
One of the most pressing matters that holds back robots from taking on more tasks and reach a widespread deployment in society is their limited ability to understand human communication and take situation-appropriate actions. This PhD position is dedicated to addressing this gap by developing the underlying data-driven models that enable a robot to engage with humans in a socially aware manner.
In order to support long-term interaction, robots need rich models of interaction that include their social context and allow them to act appropriately when faced with uncertainty. Humans use a range of verbal and non-verbal cues to regulate their interactions and are able to adapt how they communicate and cooperate to fit the needs and preferences of their interaction partners. Personalization and adaptation is needed to enable robots to assist people with varying backgrounds and abilities.
The successful applicant will develop machine-learning based and knowledge modelling techniques applied to multi-sensor data (video, audio etc.) of human behaviour that address both the complexity of the multi-modal nature of interactions and uncertainty regarding the sensor data and social situation.The applicant will design and run the experiments to evaluate the created hybrid-AI models through human-robot interaction.
1) long-term human-robot interaction
3) planning & learning for HRI
One Phd candidate will be supervised by Dr. Frank Broz and Prof. Mark Neerincx, focusing on planning and learning for long-term HRI. The other PhD candidate focused more on the NLP aspects of long-term human-robot interaction will carry out his/her PhD studies in the context of the Designing Intelligence Lab (www.di-lab.space), which is a inter-disciplinary lab between Computer Science and Industrial Design Engineering. The candidate will be supervised by Dr. Catharine Oertel Prof. Catholijn Jonker and will collaborate with design colleagues in the context of the DI lab.
To strengthen the social robotics strand of the Interactive Intelligence Group at TU-Delft these two positions are currently available with potential for collaboration.? If you're interested in either vacancy please have a look at:?
MSc in Computer Science or related field
At least 3 years of programming experience in python (java ?or C++is a plus)
Motivation to meet deadlines
Affinity to design and social science research
Interest in collaborating with colleagues from Industrial Design (DI lab)
Willingness to teach and guide students (DI lab)
The ability to work in a team, take initiative, be results oriented and systematic
TU Delft offers PhD-candidates a 4-year contract, with an official go/no go progress assessment after one year. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from ? 2395 per month in the first year to ? 3061 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.
The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.
TU Delft (Delft University of Technology)
Delft University of Technology is built on strong foundations. As?creators?of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity and aim to be as inclusive as possible (see our?Code of Conduct).?Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale.
Challenge. Change. Impact!?
Faculty Electrical Engineering, Mathematics and Computer Science
The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three disciplines - electrical engineering, mathematics and computer science. Combined, they reinforce each other and are the driving force behind the technology we use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make future-proof. We are also working on a world in which humans and computers reinforce each other. We are mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. There is plenty of room here for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1,100 employees and 4,000 students work and study in this innovative environment.
Click?here?to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.
The application procedure is 'ongoing until the position is filled so interested candidates are encouraged to apply as soon as possible and before September 20th?2021. Note that candidates who apply after the deadline may still be considered but applications before the deadline will be given priority. For further info on the content of the position please contact Dr. Catharine Oertel: C.R.M.M.Oertel@tudelft.nl or Dr. Frank Broz: F.Broz@tudelft.nl
Interested applicants should include an up-to-date curriculum vitae, letter of motivation and the names and contact information (telephone number and email address) of two references.
The letter of application should summarise (i) why the applicant wants to do a PhD, (ii) why the project is of interest to the applicant, (iii) evidence of suitability for the job, and (iv) what the applicant hopes to gain from the position
Please apply before?September 20, 2021?via the application website.
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A pre-employment screening can be part of the selection procedure.
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You can apply online. We will not process applications sent by email and/or post.
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Acquisition in response to this vacancy is not appreciated.
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| 6-30 | (2021-09-12) Research assistant at INRIA, Lille, France
Inria is opening a fixed-term research assistant position on private machine learning for
speech processing as part of the French national collaborative project ANR DEEP-PRIVACY.
The successful candidate will be part of the Magnet team in Lille, which focuses on
privacy-friendly, decentralized and/or graph-based machine learning. He/she will work in
tight collaboration with the Multispeech team in Nancy, which focuses on automatic speech
recognition and speech synthesis.
The goal of DEEP-PRIVACY is to learn automatic speech recognition (ASR) systems from
speech representations that hide speaker identity. Additional requirements such as
decentralized learning, gender fairness, or data efficiency may be considered.
Depending on her/his profile, the candidate will address the following research questions:
- how to design privacy attacks on ASR and design counter-measures;
- how to learn private representations of speech from adversarial training with many
attackers;
- how to design fair and private speech representations;
- how to adapt such methods in the decentralized setting (e.g. federated or fully
decentralized learning);
- how to formally define and measure the trade-off between accuracy, fairness, or privacy
at the global and individual levels.
Application deadline: applications will be assessed on a rolling basis; please apply as
soon as possible.
Starting date: November 1, 2021 or later
Duration: 1.5 year (renewable)
Location: Lille, France
Salary: from 2,050 to 2,130 net/month, according to experience
For more details and to apply:
https://jobs.inria.fr/public/classic/en/offres/2021-04039 (for MSc graduates)
https://jobs.inria.fr/public/classic/en/offres/2021-04034 (for PhD graduates)
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| 6-31 | (2021-09-15) Senior-level research scientist at Facebook
Facebook Reality Labs Research is seeking a senior-level research scientist in affective and behavioral computing to help craft the human-centered AR computing platform of the future. The role will involve:
? Developing and executing a cutting-edge research program with interdisciplinary collaborators aimed at developing closed-loop optimal assistance for human activities that draw heavily from ?internal? affective/emotive/cognitive contextual states;
? Developing tasks, data-collection strategies, modeling approaches, and evaluation criteria to deliver on research program objectives, with a particular focus on approaches that leverage wearable devices with multimodal biosensors;
? Working collaboratively with other research scientists to develop novel solutions and models in service of contextualized AI for augmented reality; and
? Mentoring MS/PhD interns and postdocs and collaborate closely with cross-organizational collaborators and external academic groups to advance our research objectives.
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| 6-32 | (2021-09-17)1 Post-doc and 1 PhD positions at Laboratoire de Phonétique et Phonologie* (LPP ? CNRS/Sorbonne Nouvelle), Paris, France
In the context of the project ChaSpeePro run in collaboration with the University of Geneva, the Hopitaux Universitaires de Genève and the Idiap Institute, the Laboratoire de Phonétique et Phonologie* (LPP ? CNRS/Sorbonne Nouvelle) in Paris is offering:
- a 3-year (+1) doctoral position starting from December 2021 (https://bit.ly/2XeQNf4)
- a post-doctoral position for 2-years with a possible extension of 2 more years. Ideally the position would start from December 2021, but later starting date might be considered (https://bit.ly/2VFQWr5).
The general goal of the project is to better characterize the processes linked to the encoding of invariant speech units into articulated speech, and their disorders (in dysarthria and apraxia of speech). This project follows the MoSpeeDi project described here: https://www.unige.ch/fapse/mospeedi/.
Within the scope of this project, articulatory and acoustic data will be collected at the LPP to investigate questions related to:
- The temporal organization and coordination of speech units at different levels (e.g., gesture, syllable, word, phrases)
- Stability and flexibility of the speech production system (e.g., speaker-specific strategies and adaptation to different speech task demands)
- Articulatory vs. acoustic manifestations of spatio-temporal reductions in speech
Within this Swiss-French collaborative project, the candidates will join the team under the supervision of Cécile Fougeron and in close collaboration with Anne Hermes and Leonardo Lancia.
The Laboratoire de Phonétique et Phonologie (CNRS/Sorbonne Nouvelle, https://lpp.in2p3.fr/) is a research and teaching unit in experimental phonetics and phonology. It is located in the 5th arrondissement in Paris. The lab offers a diverse and fair working environment in a small and dynamic lab.
More information on the positions and online application procedure can be found @:
- https://bit.ly/2XeQNf4 for the doctoral position
- https://bit.ly/2VFQWr5 for the post-doc position
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| 6-33 | (2021-09-20) OPEN-RANK FACULTY POSITIONS IN COMPUTER SCIENCE AT THE UNIVERSITY OF TEXAS AT EL PASO (UTEP), TX, USA
The University of Texas at El Paso is seeking a colleague to join the Computer Science faculty in the broad area of Spoken Language Processing.
OPEN-RANK FACULTY POSITIONS IN COMPUTER SCIENCE AT THE UNIVERSITY OF TEXAS AT EL PASO (UTEP)
The Department of Computer Science at UTEP invites applications for two open-rank faculty positions starting fall 2022 with preference for the areas of Spoken Language Processing, Machine Learning, Computer Systems, or Software Engineering. To view the full ad and apply, please visit https://utep.interviewexchange.com/jobofferdetails.jsp?JOBID=136383 or https://www.utep.edu/employment.
Informal inquiries can be addressed to Nigel Ward, nigel@utep.edu .
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| 6-34 | (2021-09-23) Young researchers in NLP at L3i, La Rochelle, France
Cross-lingual and cross-domain terminology alignment
Interested in joining a young NLP group of 10+ people located in a historical town by the Atlantic Ocean? And walk 10 minutes from the lab to the beach. We have open positions in the context of 2 ongoing Horizon 2020 projects: Embeddia and NewsEye as well as related projects. In 2020-2021, we have among others published long papers in CORE A* and A conferences ACL, JCDL, CoNLL, ICDAR, COLING, ICADL, etc.
Location: L3i laboratory, La Rochelle, France
Duration: 2 years (1+1), with possible further extension
Net salary range: 2100?-2300 ? monthly
Context: H2020 Embeddia project and regional project Termitrad
Start: 1 January 2022
Keywords: terminology alignment, cross-lingual word embeddings, named-entity recognition and linking, deep/machine learning, statistical NLP, (text) mining.
Applications are invited for a postdoctoral researcher position around the topic of project Termitrad: keyword and terminology alignment 1) across languages and 2) across domains. In short, the overall objective of the project is to improve the relevance of the keywords describing research papers (and, time allowing, the quality of abstracts). One the one hand (cross-lingual alignment), we will rely on a corpora of journal articles with both French and English keywords and abstracts, both in as written by authors and in versions curated by experts. On the other hand (crossdomain alignment), we will work with use cases provided by researchers from different fields using different terms to describe similar concepts.
To address this very project, the project team will consist of senior staff, 2 post-doctoral researchers and 2-3 PhD students, one of which is jointly supervised in the Józef Stefan Institute in Ljubljana, coordinator of H2020 Embeddia. In this context, you will first be in charge of building a state of the art of existing related approaches, tools and resources, then to conduct further research and experiments, as well as participate in the supervision of PhD students.
Who we search for:
- PhD in statistical NLP, IR, or ML, ideally with further postdoctoral experience
- proven record of high-level publications in one or more of those fields
- fluency in written and spoken English (French language skills are irrelevant)
Applications including a CV and a one-page research statement discussing how the candidate's background fits requirements and topic are to be sent to by email to antoine.doucet@univ-lr.fr, strictly with the subject 'Embeddia/Termitrad postdoc application'.
Application deadline: 13 October 2021.
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| 6-35 | (2021-09-24) Research Assistant at Technische Universität Berlin , Berlin, Germany
Technische Universität Berlin offers an open position:
Research Assistant - salary grade E13 TV-L Berliner Hochschulen
under the reserve that funds are granted; part-time employment may be possible
scientific collaboration in the BMBF project “Emonymous”, possibility of extension
The majority of systems and services that are provided by computer science, electrical engineering and information technology finally are oriented on the needs of their human users. To successfully build such systems and services it is essential to investigate and understand users and their behavior when interacting with technology. From this, design principles for human-machine interfaces or classification systems can be derived and requirements for the underlying technologies can be defined.
The Quality and Usability Lab is part of TU Berlin’s Faculty IV and deals with the design and evaluation of humanmachine interaction, in which aspects of human perception, technical systems and the design of interaction are the subject of our research. We focus on self-determined work in an interdisciplinary and international team; for this we offer open and flexible working conditions that promote scientific and personal exchange and are a prerequisite for excellent results.
Fakultät IV - Elektrotechnik und Informatik - Quality and Usability Lab Reference number: IV-549/21 (starting at the earliest possible / for 2 years / closing date for applications 15/10/21)
Working field: Central is the creation and empirical research of the use of speech and language technology, which includes aspects of signal processing, machine learning, artificial intelligence and natural language processing. Specific tasks in the “Emonymous” funding project are aimed, for example, at researching and implementing anonymization in speech, while at the same time preserving emotions, speaker characteristics and intelligibility. Acoustic and linguistic (textual) content are often analyzed in multimodal models and have to be evaluated using perceptual listening tests (laboratory or crowd), e.g. in order to control speech synthesizer training. If desired and suitable, the publication and presentation of project and research results in scientific journals, at conferences and workshops can be aimed for.
The specific tasks include:
Conception, construction and evaluation of speech processing systems as well as systems for speaker characterization and transformation (e.g. ASR, emotion, intelligibility, synthesis)
Measurement, planning and optimization of quality and user experience of anonymization (Quality of Experience, User Experience)
Planning and execution of user studies (laboratory, large scale crowds)
Project communication and reporting
Publication and presentation of project and research results in scientific journals, at conferences, and in workshops as well as standardization meetings of ITU-T
Professionally experienced employees from our team support you with self-motivated familiarization within the areas of responsibility.
PhD thesis preparation is possible.
Requirements:
Successfully completed scientific university degree (Master, Diplom or equivalent)in electrical engineering, computer engineering/science, informatics, media informatics, media technology, information systems (or an equivalent technical background)
Ability to work independently in a team and good self-organization
Very good programming knowledge in Python, Matlab or similar
Good knowledge of machine learning, AI and / or NLP
Good knowledge of digital signal processing, statistics, empirical data analysis
Interest in carrying out experiments with human participants to determine quality and user experience
Language skills: English fluent in writing and speaking, German communication secure
Desire to work in an agile and lively international and interdisciplinary environmen
Please send your application with the reference number and the usual documents (one file max. 5 MB) only via email to bewerbung@qu.tu-berlin.de.
By submitting your application via email you consent to having your data electronically processed and saved. Please note that we do not provide a guaranty for the protection of your personal data when submitted as unprotected file.
Please find our data protection notice acc. DSGVO (General Data Protection Regulation) at the TU staff department homepage: https://www.abt2-t.tuberlin.de/menue/themen_a_z/datenschutzerklaerung/ or quick access 214041.
To ensure equal opportunities between women and men, applications by women with the required qualifications are explicitly desired. Qualified individuals with disabilities will be favored. The TU Berlin values the diversity of its members and is committed to the goals of equal opportunities.
Technische Universität Berlin - Der Präsident -, Fakultät IV, Quality and Usability Lab, Prof. Dr.-Ing. Möller, Sekr. TEL 18,Ernst-Reuter-Platz 7, 10587 Berlin
The vacancy is also available on the internet at
https://www.personalabteilung.tu-berlin.de/menue/jobs/
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| 6-36 | (2021-09-27) PhD at KTH, Stockholm, Sweden
The School of Electrical Engineering and Computer Science (EECS) at the KTH Royal Institute of Technology announces a Ph.D position in Multimodal Machine Learning for Human-Robot Interaction at the division of Speech, Music and Hearing (TMH).
ABOUT KTH
KTH Royal Institute of Technology in Stockholm has grown to become one of Europe?s leading technical and engineering universities, as well as a key center of intellectual talent and innovation. We are Sweden?s largest technical research and learning institution and home to students, researchers and faculty from around the world. Our research and education covers a wide area including natural sciences and all branches of engineering, as well as in architecture, industrial management, urban planning, history and philosophy.
PROJECT DESCRIPTION
In this project the student will design, develop, and evaluate a telepresence platform specifically developed for collecting multimodal data for posterior automation. Unsupervised and supervised multimodal machine learning models alongside multimodal fusion techniques will be explored to evaluate the quality of the telepresence platform. Mixed reality technologies will also be explored for the creation of the telepresence platform as they offer exciting opportunities for data collection (and consequent learning of multimodal models of social behaviour). Users? mixed reality headsets allow for extracting multiple modalities such as real-time head-pose, eye-gaze information, pupil dilation, and high framerate Point of View (PoV) video data.
This position is partially funded by a project on 'Using Neuroimaging Data for Exploring Conversational Engagement in Human-Robot Interaction'. This project will leverage a multidisciplinary research collaboration with Julia Uddén from the Linguistics department at Stockholm University where we will aim to study social robotics by exploring the modality of observing underlying neural processes of people that are observing, interacting with, and controlling robots. Understanding these neural processes and how they integrate with other modalities will help us provide contributions to the research areas of Human-Robot Interaction, Artificial Intelligence, Psycho- and Neurolinguistics and Neurobiology of Language.
The starting date is open for discussion, although we would like the successful candidate to start at the beginning of 2022.
QUALIFICATIONS
The candidate must have a degree in Computer Science or related fields. Documented written and spoken English and programming skills are required. Experience with robotics, human-computer interaction, mixed-reality, neuroscience or machine learning is important.
HOW TO APPLY
The application should include:
1. Curriculum vitae.
2. Transcripts from University/College.
3. Brief description of why the applicant wishes to become a doctoral student.
The application documents must be uploaded using KTH's recruitment system. More information here:
https://www.kth.se/en/om/work-at-kth/lediga-jobb/what:job/jobID:427059
The application deadline is ** October 15, 2020 **
André Pereira
Researcher
KTH Royal Institute of Technology
School of Electrical Engineering and Computer Science
Division of Speech, Music and Hearing (TMH)
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| 6-37 | (2021-09-28) Ingenieur de recherche en informatique, LORIA,, Nancy, France
H/F Ingénieur de recherche en informatique ? développement d'une plateforme multimodale
Au LORIA à Nancy.
Les détails de l?offre et les modalités de candidature se trouvent sur le site du CNRS :
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| 6-38 | (2021-09-26) Fully funded PhD at the Science Foundation Ireland Center for Research Training in Advanced Networks for Sustainable Societies, Ireland
The Science Foundation Ireland Centre for Research Training in Advanced Networks for Sustainable Societies (https://www.advance-crt.ie/), Munster Technological University (www.mtu.ie) and GREYC UMR CNRS 6072 - Groupe de Recherche en Informatique, Image, et Instrumentation de Caen, University of Caen Normandy, France (https://www.greyc.fr/en/home/) invite applications for a fully funded dual Degree PhD (Cotutelle) position in Text Generation for Mental Health. The successful PhD candidate will be registered at both universities (Munster Technological University, Ireland and University of Caen Normandy, France).
The SFI Centre for Research Training in Advanced Networks for Sustainable Societies focuses on enabling technologies for future hyper-networks, including concepts such as network virtualization, dependable communications, Internet of Things, data driven network management and applications in sustainable and independent living. This centre will train the next generation of researchers who will seek solutions to the technical and societal challenges of global hyper-connectivity.
Vision
'? train the next generation of doctoral graduates at the interface of technologies and social sciences, graduates who can stimulate socially-responsible and inclusive creativity and innovation in the fields of advanced communications. Our aim is to ensure that the next generations of communications technology are developed with human and societal benefit as a priority objective.'
The GREYC lab, France realizes research works in the field of digital science. It has 7 research groups with faculty members from ENSICAEN, UNICAEN and CNRS, PhD students and administrative & technical members. Studies focus on fundamental and methodological aspects ? modelling, new concepts ? and also practical achievements: development of applications and software platforms, design and production of electronic devices.
Funding Notes & Eligibility Criteria
The ADVANCE CRT-GREYC postgraduate programme offers excellent student a fully-funded dual PhD where they will receive a tax-free stipend (in Ireland) of approx. ?18,500 per year for up to four years including EU tuition fees, research and equipment costs and all costs associated with training related covered.
Eligibility criteria & application process
We invite applications from individuals who hold at least a 2.1 honours undergraduate degree in relevant disciplines such as Computer Science, Computer Engineering, Electrical and Electronic Engineering or related disciplines with strong programming skills.
Application Process
Interested candidates can send an application with the following documents directly to Dr Mohammed Hasanuzzaman (mohammed.hasanuzzaman@mtu.ie) and Prof. Gaël Dias (gael.dias@unicaen.fr).
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Full transcripts and certificates for primary and highest degree(s); GPA/degree class.
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A detailed CV (maximum 3 pages)
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Evidence of English language proficiency for non-native speakers based on IELTS (or similar) score of 6.5 (or similar local requirements)
The deadline for applications is the 9th of October 2021.
Diversity
To help address gender under-representation in science, applications from female applicants are strongly encouraged, as are those from international students and other under-represented groups. This reflects each of the supervisory institutions commitment to providing a diverse and open environment for students and faculty.
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