|
 |
ISCApad #283 |
| Monday, January 10, 2022 by Chris Wellekens |
6 Jobs
| 6-1 | (2021-08-04) Several Open Positions at KUIS AI Center, Koc University, Istanbul, TurkeySeveral Open Positions at KUIS AI CenterKoc University, Istanbul, Turkey
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:
2)Open Post-Doc Positions (3 positions)
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)
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.
| ||||||||||||||
| 6-2 | (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.
| ||||||||||||||
| 6-3 | (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 information In 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 - France Application Application 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-cdi Important dates ? September 24, 2021 : application deadline ? October 25-26 and November 4-5: interviews (by visio-conference eventually) Winter 2021/22: beginning Contact : Stephan Clémençon (Head of the S2A group) stephan.clemencon@telecom-paris.fr Florence d?Alché (Holder of the Chair DSAIDIS) florence.dalche@telecom-paris.fr For more info on being an Associate Professor at Telecom Paris, contact rh@telecom-paris.fr Other web Sites : Image, Data, Signal Department: web link LTCI lab: web link S2A team: web link Télécom Paris: web link
| ||||||||||||||
| 6-4 | (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.
| ||||||||||||||
| 6-5 | (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
| ||||||||||||||
| 6-6 | (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
| ||||||||||||||
| 6-7 | (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.
Topics of interest:
1) long-term human-robot interaction
2) affective computing
2) NLP&argument-mining
3) planning & learning for HRI
4) assistive robotics
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:?
Requirements
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
Conditions of employment
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.
Additional information
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
Application procedure
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.
| ||||||||||||||
| 6-8 | (2021-09-12) Research assistant at INRIA, Lille, France
| ||||||||||||||
| 6-9 | (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.
The complete job description can be accessed here: https://www.facebook.com/careers/v2/jobs/283289239909563/
| ||||||||||||||
| 6-10 | (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:
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
| ||||||||||||||
| 6-11 | (2021-09-20) OPEN-RANK FACULTY POSITIONS IN COMPUTER SCIENCE (incl. Spoken Language Processing) 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 .
| ||||||||||||||
| 6-12 | (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
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.
- 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.
| ||||||||||||||
| 6-13 | (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/
| ||||||||||||||
| 6-14 | (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)
| ||||||||||||||
| 6-15 | (2021-09-28) Ingenieur de recherche en informatique, LORIA,, Nancy, France H/F Ingénieur de recherche en informatique ? développement d'une plateforme multimodale
| ||||||||||||||
| 6-16 | (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).
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.
| ||||||||||||||
| 6-17 | (2021-10-20) PhD position Orléans/Grenble France Lieu : Orléans/Grenoble, France Selon les avancées, les recherches pourront s'étendre à d'autres tâches du TAL : Bibiographie sélective Encadrement Calendrier : Date limite d?envoi des dossiers : 05 novembre 2021 Les dates des auditions seront communiquées aux candidat.e.s retenu.e.s sur dossier.
| ||||||||||||||
| 6-18 | (2021-10-21) Three fully-funded PhD positions on early prosodic development at Utrecht University The Netherlands Three fully-funded PhD positions on early prosodic development at Utrecht University
These positions are part of a new Dutch Research Council project ‘SoundStart’ on early prosodic development led by Professor Aoju Chen at Utrecht University. Children show knowledge of prosody (i.e., melody and rhythm) of their native language already at birth and thrive on it in early language and communication development. However, how children learn prosody so early is still unknown. Taking an interdisciplinary and crosslinguistic approach, SoundStart aims to discern the role of innate mechanisms, uncover learning mechanisms in the auditory modality underlying development spanning prenatal and after-birth periods, and shed light on the role of visual cues to prosody (i.e., speech-accompanying gestures) in after-birth periods. PhD projects 1 and 2 will be concerned with the first two goals in the learning of prosodic phrasing (i.e., grouping sequences of sounds into meaningful units in speech streams) and prosodic form-meaning mappings (i.e. associating prosodic patterns with communicative functions), PhD project 3 with the third goal in both areas of prosodic development. We are seeking to hire highly motivated, driven and talented MA graduates to take on the PhD projects, starting 1 February 2022. A later starting date is negotiable.
In this research programme you will work within an interdisciplinary team, closely collaborating with researchers from linguistics, neuroscience, psycholinguistics, psychology and neonatology at Utrecht University and the University Medical Centre Utrecht. You will receive assistance from student assistants in data collection (in the Netherlands and abroad) and/or data processing and have the opportunity to develop your academic teaching skills during your project.
Do you want to play a key role in this new exciting research programme on early prosodic development? Read more and apply! The application deadline is 8 November, 2021.
For more information about these positions, please contact Professor Aoju Chen at aoju.chen@uu.nl.
---- Prof. dr. Aoju Chen Chair of Language Development in Relation to Socialisation and Identity Head of the English Language and Culture Division Leader of VICI research group SoundStart Department of Languages, Literature and Communication & Utrecht Institute of Linguistics - OTS Utrecht University The Netherlands
| ||||||||||||||
| 6-19 | (2021-10-25) Ingenieur de développement, INRIA,Nancy, France L'équipe Multispeech d'Inria Nancy recrute un ingénieur permanent dont la mission principale sera de piloter et contribuer au développement d'un assistant virtuel multimodal évolutif, à partir de briques logicielles open source et/ou issues de l'équipe, à des fins de recherche et de transfert industriel.
Fiche de poste: voir pages 9-10 du fichier https://www.inria.fr/sites/default/files/2021-10/Fiches_poste_ingenieurs_permanents.pdf
Candidature en ligne: https://www.inria.fr/fr/concours-externes Date butoir: 31/10/2021.
| ||||||||||||||
| 6-20 | (2021-10-26) Master internships at TALEP, Marseille, France L'équipe TALEP de Marseille propose plusieurs stages de M2 en TAL à partir de février 2022 :
The TALEP team (Marseille, France) has several master internship offers in NLP starting in Feb 2022:
* Joint speech segmentation and syntactic analysis
* Syntactic analysis of speech without transcription* Matching contextual and definitional embeddings for a sense-aware reading assistant * Using deep learning to study children?s multimodal behavior in face-to-face conversation * Using interpretability methods to explain Vision-Language models for medical applications * Impact of language evolution in historical texts on NLP models * Fidélité et exactitude de la génération dans les systèmes de génération de texte
* ...
Liste complète et détails / full list and details : https://www.lis-lab.fr/offre-de-stage/
Candidatez maintenant pour découvrir un environnement scientifique stimulant dans une ville vibrante et ensoleillée :-)
Apply now to discover a stimulating scientific environment in a vibrant sunny city :-)
-- Carlos RAMISCH
http://pageperso.lis-lab.fr/carlos.ramisch
Assistant professor at LIS/TALEP and Aix Marseille University, France
| ||||||||||||||
| 6-21 | (2021-11-12) Internships at IRIT, Toulouse, France L’équipe SAMoVA de l’IRIT à Toulouse propose plusieurs stages en 2022 :
| ||||||||||||||
| 6-22 | (2021-11-13)Master internship at IRISA, Lannion, France EXPRESSION Team IRISA LANNION - Proposal for an internship for a Research Master in Computer Science
Title: Joint training framework for text-to-speech and voice conversion
Text-to-speech and voice conversion are two distinct speech generation techniques. Text-to-speech (TTS) is a process that generates speech from a sequence of graphemes or phonemes. Voice conversion is the conversion of speech from a source voice to a target voice. These processes find their application in domains such as Computer Assisted Language Learning, for example.
However, these two processes share some bricks, particularly the vocoder that generates speech from acoustic characteristics or the spectrogram. The quality of these two technologies has been significantly improved thanks to the availability of massive databases, the power of computing machines, and the deep learning paradigm implementation. On the other hand, restoring or controlling expressiveness, and more generally considering suprasegmental information, remains a major challenge for these two technologies.
This internship topic aims at setting up a common framework for both technologies. We aim at a joint deep learning framework to generate speech (target voice) from either speech (source voice) or text.
It will be supervised by members of the EXPRESSION team (IRISA): Aghilas Sini, Pierre Alain, Damien Lolive, and Arnaud Delhay-Lorrain.
Please send your application (CV + cover letter) before 10/01/2022 to à aghilas.sini@irisa.fr,palain@irisa.fr, damien.lolive@irisa.fr, arnaud.delhay@irisa.fr
Start date: 01/02/2022 (flexible)
======================
| ||||||||||||||
| 6-23 | (2021-11-15) Stage en reconnaissance automatique de la parole chez Zaion, France ====== Offre de stage en reconnaissance automatique de la parole ======== Nous proposons une offre de stage au sein de Zaion, portant sur le développement de solutions de Reconnaissance Automatique de la Parole adaptées au contexte de la relation client, sur de nouvelles langues (niveau M2).
Merci de transférer si vous connaissez des étudiant.e.s à la quête de telle opportunité. Description et contacts :
| ||||||||||||||
| 6-24 | (2021-11-26) Four research internships at SteelSeries France R&D team The SteelSeries France R&D team (former Nahimic R&D team) is glad to open 4 research internship positions for 2022. The selected candidates will be working on one of the following topics (more details in attached):
- Audio media classification
- Audio source classification
- Audio source separation
- Real-time speech restoration
Please reply/apply to nathan.souviraa-labastie@steelseries.com.
Audio media classification Master internship, Lille (France), 2022
Advisors — Pierre Biret, R&D Engineer, pierre.biret@steelseries.com — Nathan Souviraà-Labastie, R&D Engineer, PhD, nathan.souviraa-labastie@steelseries.com
Company description
SteelSeries is a leader in gaming peripherals focused on quality, innovation and functionality, and the fastest growing major gaming headset brand globally. Founded in 2001, SteelSeries improves performance through first-to-market innovations and technologies that enable gamers to play harder, train longer, and rise to the challenge. SteelSeries is a pioneer supporter of competitive gaming tournaments and eSports and connects gamers to each other, fostering a sense of community and purpose. Nahimic has joined the SteelSeries family in 2020 to bolster reputation of industry-leading gaming audio performance across both hardware and software. Nahimic is the leading 3D gaming audio software editor with more than 150 man-years of research and development in gaming industry. Their team gathers the rare combination of world class audio processing engineers and software geniuses based across France, Singapore and Taiwan. They are the worldwide leader in PC audio gaming software that are embedded in millions of gaming devices, from gaming headsets to the most powerful gaming PCs by brands such as MSI, Dell, Asus, Gigabyte, etc. Their technology offers the most precise and immersive sound for gamers that allows them to be more efficient in any game and have more immersive feeling. We wish to meet passionate people full of energy and motivations, ready to achieve great challenges to exhale everyone’s audio experience. We are currently looking for a AUDIO SIGNAL PROCESSING / MACHINE LEARNING RESEARCH INTERN to join the R&D team of SteelSeries’ Software & Services Business Unit in our French office (former Nahimic R&D team).
Subject
The target of the internship is to build a model able to classify audio streams into multiple media classes (classes description upon request).The audio classification problem will be addressed using supervised machine learning. Hence, the first step of the internship will be to collect data and build a balanced corpus for such an audio classification problem. Fortunately, massive audio content for most potential classes are available within the company and this task should not be an important burden. Once the corpus is built, the intern will have to either tune the parameters of an already existing internal model or develop a more adapted model from the state of the art [1] [2] [4] that still satisfy the «real-time» constraint. A more advanced step of the internship would be to define a more precise media type classification with for instance sub-types within a same category.Once the relevant classes have been identified, the intern will have to incorporate such changes in his classification algorithm and framework. As the intern will receive support to turn his model into an in-product real-time prototype, this internship is a rare opportunity to bring research to product in such a short time frame.
Skills
Who are we looking for ? Preparing an engineering degree or a master’s degree, you preferably have knowledge in the development and implementation of advanced algorithms for digital audio signal processing. Machine learning skills is a plus. 1 Whereas not mandatory, notions in the following various fields would be appreciated : Audio, acoustics and psychoacoustics - Audio effects in general : compression, equalization, etc. - Machine learning and artificial neural networks. - Statistics, probabilist approaches, optimization. - Programming language : Matlab, Python, Pytorch, Keras, Tensorflow. - Voice recognition, voice command. - Computer programming and development : Max/MSP, C/C++/C#. - Audio editing software : Audacity, Adobe Audition, etc. - Scientific publications and patent applications. - Fluent in English and French. - Demonstrate intellectual curiosity.
Other offers https://nahimic.welcomekit.co/
https://www.welcometothejungle.co/companies/nahimic/jobs
Références
[1] DCase Challenge Low-Complexity Acoustic Scene Classification with Multiple Devices. url : http: //dcase.community/challenge2021/task-acoustic-scene-classification-results-a.
[2] B. Kim et al. Domain Generalization on Efficient Acoustic Scene Classification using Residual Normalization. 2021. arXiv : 2111.06531 [cs.SD].
[3] Nahimic on MSI. url : https://fr.msi.com/page/nahimic.
[4] sharathadavanne. seld-dcase2021. https://github.com/sharathadavanne/seld-dcase2021. 2021
Audio source classification Master internship, Lille (France), 2022
Advisors — Nathan Souviraà-Labastie, R&D Engineer, PhD, nathan.souviraa-labastie@steelseries.com — Pierre Biret, R&D Engineer, pierre.biret@steelseries.com Company description
SteelSeries is a leader in gaming peripherals focused on quality, innovation and functionality, and the fastest growing major gaming headset brand globally. Founded in 2001, SteelSeries improves performance through first-to-market innovations and technologies that enable gamers to play harder, train longer, and rise to the challenge. SteelSeries is a pioneer supporter of competitive gaming tournaments and eSports and connects gamers to each other, fostering a sense of community and purpose. Nahimic has joined the SteelSeries family in 2020 to bolster reputation of industry-leading gaming audio performance across both hardware and software. Nahimic is the leading 3D gaming audio software editor with more than 150 man-years of research and development in gaming industry. Their team gathers the rare combination of world class audio processing engineers and software geniuses based across France, Singapore and Taiwan. They are the worldwide leader in PC audio gaming software that are embedded in millions of gaming devices, from gaming headsets to the most powerful gaming PCs by brands such as MSI, Dell, Asus, Gigabyte, etc. Their technology offers the most precise and immersive sound for gamers that allows them to be more efficient in any game and have more immersive feeling. We wish to meet passionate people full of energy and motivations, ready to achieve great challenges to exhale everyone’s audio experience. We are currently looking for a AUDIO SIGNAL PROCESSING / MACHINE LEARNING RESEARCH INTERN to join the R&D team of SteelSeries’ Software & Services Business Unit in our French office (former Nahimic R&D team).
Subject
The target of the internship is to build a model able to classify audio sources. And by audio sources, we mean sources present inside a predetermined given media such as music, movies or video games, e.g., instruments in the case of music. The audio classification problem will be addressed using supervised machine learning. The intern would not start his project from scratch as data and classification code from other projects can be re-used with minor adaptation (description upon request). Once the corpus is reshaped for classification, the intern will have to either tune the parameters of an already existing internal model or develop a more adapted model from the state of the art [1] [3] [5] that still satisfy strong real-time constraint. Multi-task approach A more advanced step of the internship would be to explore multi-task models. The two tasks of target would be 1/ the classification task that the intern would have previously addressed, 2/ the audio source separation task on the same data type. This is a very challenging machine learning problem, especially because the different tasks are heterogeneous (classification, regression, signal estimation), contrary to homogeneous multi-task classification where a classifier is able to address different classification task. Moreover, just a few study are targeting audio heteregeneous multi-task (exhaustive list from advisors knowledge [2, 6, 7, 4]). Potential advantages of the multi-task approach are performance improvement for the main/principal task and computational cost reduction in products, as several tasks are achieved at the same time. Previous internal bibliographic work and network architecture could be used as starting point for this approach.
Skills
Who are we looking for ? Preparing an engineering degree or a master’s degree, you preferably have knowledge in the development and implementation of advanced algorithms for digital audio signal processing. Machine learning skills is a plus. Whereas not mandatory, notions in the following various fields would be appreciated : Audio, acoustics and psychoacoustics - Machine learning and artificial neural networks. - Audio effects in general : compression, equalization, etc. - Statistics, probabilist approaches, optimization. - Programming language : Matlab, Python, Pytorch, Keras, Tensorflow. - Sound spatialization effects : binaural synthesis, ambisonics, artificial reverberation. - Voice recognition, voice command. - Voice processing effects : noise reduction, echo cancellation, array processing. - Computer programming and development : Max/MSP, C/C++/C#. - Audio editing software : Audacity, Adobe Audition, etc. - Scientific publications and patent applications. - Fluent in English and French. - Demonstrate intellectual curiosity.
Other offers
https://nahimic.welcomekit.co/ https://www.welcometothejungle.co/companies/nahimic/jobs
Références
[1] DCase Challenge Low-Complexity Acoustic Scene Classification with Multiple Devices. url : http: //dcase.community/challenge2021/task-acoustic-scene-classification-results-a.
[2] P. Georgiev et al. « Low-resource Multi-task Audio Sensing for Mobile and Embedded Devices via Shared Deep Neural Network Representations ». In : Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 1.3 (sept. 2017), 50 :1-50 :19.
[3] B. Kim et al. Domain Generalization on Efficient Acoustic Scene Classification using Residual Normalization. 2021. arXiv : 2111.06531 [cs.SD].
[4] H. Phan et al. « On multitask loss function for audio event detection and localization ». In : arXiv preprint arXiv :2009.05527 (2020).
[5] sharathadavanne. seld-dcase2021. https://github.com/sharathadavanne/seld-dcase2021. 2021.
[6] G. P. Stéphane Dupont Thierry Dutoit. « Multi-task learning for speech recognition : an overview ». In : 24th European Symposium on Artificial Neural Networks 1 (2016).
[7] D. Stoller, S. Ewert et S. Dixon. « Jointly Detecting and Separating Singing Voice : A Multi-Task Approach ». en. In : arXiv :1804.01650 [cs, eess] (avr. 2018). arXiv : 1804.01650.
Audio source separation Master internship, Lille (France), 2022
Advisors — Nathan Souviraà-Labastie, R&D Engineer, PhD, nathan.souviraa-labastie@steelseries.com — Damien Granger, R&D Engineer, damien.granger@steelseries.com
Company description
SteelSeries is a leader in gaming peripherals focused on quality, innovation and functionality, and the fastest growing major gaming headset brand globally. Founded in 2001, SteelSeries improves performance through first-to-market innovations and technologies that enable gamers to play harder, train longer, and rise to the challenge. SteelSeries is a pioneer supporter of competitive gaming tournaments and eSports and connects gamers to each other, fostering a sense of community and purpose. Nahimic has joined the SteelSeries family in 2020 to bolster reputation of industry-leading gaming audio performance across both hardware and software. Nahimic is the leading 3D gaming audio software editor with more than 150 man-years of research and development in gaming industry. Their team gathers the rare combination of world class audio processing engineers and software geniuses based across France, Singapore and Taiwan. They are the worldwide leader in PC audio gaming software that are embedded in millions of gaming devices, from gaming headsets to the most powerful gaming PCs by brands such as MSI, Dell, Asus, Gigabyte, etc. Their technology offers the most precise and immersive sound for gamers that allows them to be more efficient in any game and have more immersive feeling. We wish to meet passionate people full of energy and motivations, ready to achieve great challenges to exhale everyone’s audio experience. We are currently looking for a AUDIO SIGNAL PROCESSING / MACHINE LEARNING RESEARCH INTERN to join the R&D team of SteelSeries’ Software & Services Business Unit in our French office (former Nahimic R&D team).
Approaches and topics for the internship Audio source separation consists in extracting the different sound sources present in an audio signal, in particular by estimating their frequency distributions and/or spatial positions. Many applications are possible from karaoke generation to speech denoising. In 2020, our separation approaches [11, 1] were equaling the state of the art [12, 13] on a music separation task and many tracks of improvement are possible in terms of implementations (details hereafter). The selected candidate will work on one or several of the following topics according to her/his aspirations, skills and bibliographic outcomes. In addition to those topics, the candidates can also make their own topic proposal. She/he will also have the chance to work on our internal substantive datasets. New core algorithm Machine learning is a fast changing research domain and an algorithm can move from being state of the art to being obsolete in less than a year (see for instance the recent advances in music source separation [9, 3]). The task would be to try recent powerful neural network approaches like recent architectures or unit types that proved benefit in other research fields. For instance, the encoding and decoding part of [15] shows huge benefit compared to traditional audio codec. Other research domains outside audio (like computer vision) might be considered as sources of inspiration. For instance, the approaches in [14, 6] have shown promising results on other tasks and previous internal work [1] managed to bring those benefits to audio source separation. Conversely, approaches like [10, 5] were tested without benefit for the separation tasks that we target. 1 Overall, the targeted benefits of a new approach can be of two kinds, either to bring improvements in terms of audio separation performances, either to reduce the computational costs (mainly CPU/GPU load, RAM usage). Extension to multi-source Another challenging problem would be to estimate all the different sources with a single network, either by selecting wich source to output but with a single network such as in [7], either by outputting all sources at the same time. In the case of music, most of the state of the art approaches [12] had historically addressed the backing track problem (i.e., karaoke for instruments) as a one instrument versus the rest problem, hence using specific networks for each instruments when multiple instruments are present in the mix. Pruning Beside testing new architectures or unit types, pruning could be a simple and effective way to reduce computational costs. The original pruning principle is to remove the less influent neural units in order to avoid overfitting. We would mainly be interested in reducing the total amount of units and parameters.The theoretical and domain agnostic literature [16, 4, 8], as well as the audio specific literature [2] will be explored. As the selected candidate would work on our most advanced model, this subject is the opportunity to have a direct impact on the company in such a short time frame.
Skills
Who are we looking for ? Preparing an engineering degree or a master’s degree, you preferably have knowledge in the development and implementation of advanced algorithms for digital audio signal processing. Machine learning skills is a plus. Whereas not mandatory, notions in the following various fields would be appreciated : Audio, acoustics and psychoacoustics - Machine learning and artificial neural networks. - Audio effects in general : compression, equalization, etc. - Statistics, probabilist approaches, optimization. - Programming language : Matlab, Python, Pytorch, Keras, Tensorflow. - Sound spatialization effects : binaural synthesis, ambisonics, artificial reverberation. - Voice recognition, voice command. - Voice processing effects : noise reduction, echo cancellation, array processing. - Computer programming and development : Max/MSP, C/C++/C#. - Audio editing software : Audacity, Adobe Audition, etc. - Scientific publications and patent applications. - Fluent in English and French. - Demonstrate intellectual curiosity.
Other offers
https://nahimic.welcomekit.co/ https://www.welcometothejungle.co/companies/nahimic/jobs
Internship position at Telecom-Paris on Deep learning approaches for social computing
*Place of work* Telecom Paris, Palaiseau (Paris outskirt)
*Starting date* From February 2021(but can start later)
*Duration* 4-6 months
*Context* The intern will take part in the REVITALISE project, funded by ANR. The research activity of the internship will bring together the research topics of Prof. Chloé Clavel [Clavel] of the S2a [SSA] team at Telecom-Paris– social computing [SocComp] - and Dr. Mathieu Chollet [Chollet] from University of Glasgow – multimodal systems for social skills training, and Dr Beatrice Biancardi [Biancardi] – Social Behaviour Modelling from CESI Engineering School, Nanterre.
* Candidate profile* As a minimum requirement, the successful candidate should have: • A master degree in one or more of the following areas: human-agent interaction, deep learning, computational linguistics, affective computing, reinforcement learning, natural language processing, speech processing • Excellent programming skills (preferably in Python) • Excellent command of English • The desire to do an academic thesis at Telecom-Paris after the internship
*How to apply* The application should be formatted as **a single pdf file** and should include: • A complete and detailed curriculum vitae • A cover letter • The contact of two referees The pdf file should be sent to the two supervisors: Chloé Clavel, Beatrice Biancardi and Mathieu Chollet: chloe.clavel@telecom-paris.fr, bbiancardi@cesi.fr, mathieu.chollet@glasgow.ac.uk
Multimodal attention models for assessing and providing feedback on users’ public speaking ability
*Keywords* human-machine interaction, attention models, recurrent neural networks, Social Computing, natural language processing, speech processing, non-verbal behavior processing, multimodality, soft skills, public speaking
*Supervision* Chloé Clavel, Mathieu Chollet, Beatrice Biancardi
*Description* Oral communication skills are essential in many situations and have been identified as core skills of the 21st century. Technological innovations have enabled social skills training applications which hold great training potential: speakers’ behaviors can be automatically measured, and machine learning models can be trained to predict public speaking performance from these measurements and subsequently generate personalized feedback to the trainees. The REVITALISE project proposes to study explainable machine learning models for the automatic assessment of public speaking and for automatic feedback production to public speaking trainees. In particular, the recruited intern will address the following points: - identify relevant datasets for training public speaking and prepare them for model training - propose and implement multimodal machine learning models for public speaking assessment and compare them to existing approaches in terms of predictive performance. - integrate the public assessment models to produce feedback a public speaking training interface, and evaluate the usefulness and acceptability of the produced feedback in a user study The results of the project will help to advance the state of the art in social signal processing, and will further our understanding of the performance/explainability trade-off of these models.
The compared models will include traditional machine learning models proposed in previous work [Wortwein] and sequential neural approaches (recurrent networks) that integrate attention models as a continuation of the work done in [Hemamou], [BenYoussef]. The feedback production interface will extend a system developed in previous work [Chollet21].
Selected references of the team: [Hemamou] L. Hemamou, G. Felhi, V. Vandenbussche, J.-C. Martin, C. Clavel, HireNet: a Hierarchical Attention Model for the Automatic Analysis of Asynchronous Video Job Interviews. in AAAI 2019, to appear [Ben-Youssef] Atef Ben-Youssef, Chloé Clavel, Slim Essid, Miriam Bilac, Marine Chamoux, and Angelica Lim. Ue-hri: a new dataset for the study of user engagement in spontaneous human-robot interactions. In Proceedings of the 19th ACM International Conference on Multimodal Interaction, pages 464–472. ACM, 2017. [Wortwein] Torsten Wörtwein, Mathieu Chollet, Boris Schauerte, Louis-Philippe Morency, Rainer Stiefelhagen, and Stefan Scherer. 2015. Multimodal Public Speaking Performance Assessment. In Proceedings of the 2015 ACM on International Conference on Multimodal Interaction (ICMI '15). Association for Computing Machinery, New York, NY, USA, 43–50. [Chollet21] Chollet, M., Marsella, S., & Scherer, S. (2021). Training public speaking with virtual social interactions: effectiveness of real-time feedback and delayed feedback. Journal on Multimodal User Interfaces, 1-13.
Other references: [TPT] https://www.telecom-paristech.fr/eng/ [IMTA] https://www.imt-atlantique.fr/fr [SSA] http://www.tsi.telecom-paristech.fr/ssa/# [PACCE] https://www.ls2n.fr/equipe/pacce/ [Clavel] https://clavel.wp.imt.fr/publications/ [Chollet] https://matchollet.github.io/ [Biancardi] https://sites.google.com/view/beatricebiancardi -Rasipuram, Sowmya, and Dinesh Babu Jayagopi. 'Automatic multimodal assessment of soft skills in social interactions: a review.' Multimedia Tools and Applications (2020): 1-24. -Sharma, Rahul, Tanaya Guha, and Gaurav Sharma. 'Multichannel attention network for analyzing visual behavior in public speaking.' 2018 IEEE Winter Conference on Applications of Computer Vision (WACV). IEEE, 2018. -Acharyya, R., Das, S., Chattoraj, A., & Tanveer, M. I. (2020, April). FairyTED: A Fair Rating Predictor for TED Talk Data. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 34, No. 01, pp. 338-345).
| ||||||||||||||
| 6-26 | (2021-12-18) Master or PhD internships Hi, You are in a Master or PhD program (in NLP or Speech proc.) and want to do an internship in 2022 co-supervised by
and
?
This offer is for you ! https://tinyurl.com/intern-nle-sb (You can apply online from the Web link)
—————
Joint ASR and Repunctuation for Better Machine and Human Readable Transcripts
| ||||||||||||||
| 6-27 | (2021-12-19) 2 research engineer positions ALAIA, IRIT, Toulouse, France Afin de renforcer son équipe, le laboratoire Commun ALAIA, destiné à l'Apprentissage des langues Assisté par Intelligence Artificielle, propose deux postes d'ingénieurs de recherche (12 mois). ALAIA est centré sur l'expression et la compréhension orale d'une langue étrangère cible (L2). En collaboration avec ses deux partenaires, académique (IRIT) et industriel (Archean Technologie) ainsi que des experts en didactiques de langues, les missions consisteront à concevoir, développer et intégrer des services innovants basés sur l'analyse des productions des apprenants L2, la détection et la caractérisation d'erreurs allant du niveau phonétique au niveau linguistique. Elles seront affinées en fonction du profil des personnes recrutées. Les compétences attendues portent sur le traitement automatique de la parole et du langage ainsi que les méthodes de machine learning.
Les candidatures sont à adresser à Isabelle Ferrané (isabelle.ferrane@irit.fr) et Lionel Fontan (lfontan@archean.tech). N'hésitez pas à nous contacter pour de plus amples informations.
| ||||||||||||||
| 6-28 | (2021-12-26) Research associate and postdoc at Heriot-Watt University, Edinburgh, UK 1) Research Associate in Safe Conversational AI(re-advertising) Closing date: 9th January 2022
?
We seek a candidate with experience in neural approaches to natural language generation, or closely related fields, including Vision + Language tasks.
Applicants interested in social computing tasks, such as online abuse detection and mitigation, as well as interdisciplinary candidates with a wider interest in ethical and social implications of NLP are also encouraged to apply.
The opportunity:
This is an exciting opportunity to work with a team developing safer AI methods bringing together AI researchers and researchers working on formal verification methods to researchers working on computational law. You will contribute your insight and experience into researching and developing deep learning methods for Conversational AI and closely related areas.
The project is led by Heriot-Watt University and in cooperation with the University of Edinburgh and Strathclyde, see https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/T026952/1
2) Postdoctoral Research Assistant in children's perceptions of technology
Closing date: 6th January 2022
?
We are looking for a creative and self-motivated researcher to investigate children?s knowledge and perceptions of conversational agents such as Alexa. The position is located at the University of Edinburgh's Moray House School of Education.
The opportunity:
This is an exciting opportunity to work with an interdisciplinary team of computer scientists and social psychologists at three Scottish universities on a project to address gender bias in conversational agents. You will contribute your insight and experience into researching technology with and for children to the team.
The project is led by Heriot-Watt University and in cooperation with the University of Edinburgh and Strathclyde, see https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/T024771/1
For any enquiries, please get in touch!
Prof. Verena Rieser
Heriot-Watt University, Edinburgh
https://sites.google.com/site/verenateresarieser/
| ||||||||||||||
| 6-29 | (2022-01-10) Conference coordinator, ISCA. The International Speech Communication (ISCA) [www.isca-speech.org) seeks application for a :
Conference Coordinator (f/m/d)
For a limited-term contract with 18h/week, with the perspective of extension towards an unlimited-term contract.
The International Speech Communication Association (ISCA) is a scientific non-profit organization according to the French law 1901. The purpose of the association is to promote, in an international world-wide context, activities and exchanges in all fields related to speech communication science and technology. The association is aimed at all persons and institutions interested in fundamental research and technological development that aims at describing, explaining and reproducing the various aspects of human communication by speech, e.g. phonetics, linguistics, computer speech recognition and synthesis, speech compression, speaker recognition, aids to medical diagnosis of voice pathologies.
One of the core activities of ISCA is to ensure the continuous organization of its flagship conference, Interspeech. The conference is organized each year in a different country by a different team; it typically attracts 1500 or more participants from all over the world. The role of this newly-created position of conference coordinator is to ensure a smooth organization of the conference over the years, according to well-established standards, and taking into account the aims ISCA has with the conference.
The role requires – amongst others – to take over the lead for the following activities:
Required competences:
We are looking for a self-motivated person who is enthusiastic about the organization of international scientific events, and has excellent organizational and communication skills (mostly in English). The person does not need to have a scientific background in speech communication and technology, but should be able to understand the scientific background, as well as the aims ISCA has with the organization of Interspeech conferences. A proven expertise in the organization of large-scale events is a must, and of scientific events is a plus.
The job can be carried out remotely from any location. A flexible allocation of time over the year is required, depending on the status of preparations (the conference is typically organized in September, and there is an expected increase in activity from March to September). The willingness to physically attend preparatory meetings and the conference is required.
Deadline : 15 March 2022.
| ||||||||||||||
