3.1.1 Integrating domain knowledge

State-of-the-art methods in speech and audio are based on neural networks trained for the targeted task. This paradigm faces major limitations: lack of interpretability and of guarantees, large data requirements, and inability to generalize to unseen classes or tasks. We research deep generative models as a way to learn task-agnostic probabilistic models of audio signals and design inference methods to combine and reuse them for a variety of tasks. We pursue our investigation of hybrid methods that combine the representational power of deep learning with statistical signal processing expertise by leveraging recent optimization techniques for non-convex, non-linear inverse problems. We also explore the integration of deep learning and symbolic reasoning to increase the generalization ability of deep models and to empower researchers/engineers to improve them.

3.1.2 Learning from little/no labeled data

While fully labeled data are costly, unlabeled data are cheap but provide intrinsically less information. Weakly supervised learning based on not-so-expensive incomplete and/or noisy labels is a promising middle ground. This entails modeling label noise and leveraging it for unbiased training. Models may depend on the labeler, the spoken context (voice command), or the temporal structure (ambient sound analysis). We also study transfer learning to adapt an expressive (audiovisual) speech synthesizer trained on a given speaker to another speaker for which only neutral voice data has been collected.

3.1.3 Preserving privacy

Some voice technology companies process users' voices in the cloud and store them for training purposes, which raises privacy concerns. We aim to hide speaker identity and (some) speaker states and traits from the speech signal, and evaluate the resulting automatic speech/speaker recognition accuracy and subjective quality/intelligibility/identifiability, possibly after removing private words from the training data. We also explore semi-decentralized learning methods for model personalization, and seek to obtain statistical guarantees.

3.2.1 Articulatory modeling

Articulatory speech synthesis relies on 2D and 3D modeling of the dynamics of the vocal tract from real-time MRI data. The prediction of glottis opening is also considered so as to produce better quality acoustic events for consonants. The coarticulation model developed to handle the animation of the visible articulators will be extended to control the face and the tongue. This helps characterize links between the vocal tract and the face, and illustrate inner mouth articulation to learners. The suspension of articulatory movements in stuttering speech is also studied.

3.2.2 Multimodal expressive speech

The dynamic realism of the animation of the talking head, which has a direct impact on audiovisual intelligibility, continues to be our goal. Both the animation of the lower part of the face relating to speech and of the upper part relating to the facial expression are considered, and development continues towards a multilingual talking head. We investigate further the modeling of expressivity both for audio-only and for audiovisual speech synthesis. We also evaluate the benefit of the talking head in various use cases, including children with language and learning disabilities or deaf people.

3.2.3 Categorization of sounds and prosody

Reading and speaking are basic skills that need to be mastered. Further analysis of schooling experience will allow a better understanding of reading acquisition, especially for children with some language impairment. With respect to L1/L2 language interference1, a special focus is set on the impact of L2 prosody on segmental realizations. Prosody is also considered for its implication on the structuration of speech communication, including on discourse particles. Moreover, we experiment the usage of speech technologies for computer assisted language learning in middle and high schools, and, hopefully, also for helping children learning to read.

3.3.1 Acoustic environment analysis

Audio scene analysis is key to characterize the environment in which spoken communication may take place. We investigate audio event detection methods that exploit both strongly/weakly labeled and unlabeled data, operate in real-world conditions, can discover novel events, and provide a semantic interpretation. We keep working on source localization in the presence of nearby acoustic reflectors. We also pursue our effort at the interface of room acoustics to blindly estimate room properties and develop acoustics-aware signal processing methods. Beyond spoken communication, this has many applications to surveillance, robot audition, building acoustics, and augmented reality.

3.3.2 Speech enhancement and noise robustness

We pursue speech enhancement methods targeting several distortions (echo, reverberation, noise, overlapping speech) for both speech and speaker recognition applications, and extend them to ad-hoc arrays made of the microphones available in our daily life using multi-view learning. We also continue to explore statistical signal models beyond the usual zero-mean complex Gaussian model in the time-frequency domain, e.g., deep generative models of the signal phase. Robust acoustic modeling will be achieved by learning domain-invariant representations or performing unsupervised domain adaptation on the one hand, and by extending our uncertainty-aware approach to more advanced (e.g., nongaussian) uncertainty models and accounting for the additional uncertainty due to short utterances on the other hand, with application to speaker and language recognition “in the wild”.

3.3.3 Linguistic and semantic processing

We seek to address robust speech recognition by exploiting word/sentence embeddings carrying semantic information and combining them with acoustical uncertainty to rescore the recognizer outputs. We also combine semantic content analysis with text obfuscation models (similar to the label noise models to be investigated for weakly supervised training of speech recognition) for the task of detecting and classifying (hateful, aggressive, insulting, ironic, neutral, etc.) hate speech in social media.

7.1.1 COMPRISE Voice Transformer

• Name:
  COMPRISE Voice Transformer
• Keywords:
  Speech, Privacy
• Functional Description:
  COMPRISE Voice Transformer is an open source tool that increases the privacy of users of voice interfaces by converting their voice into another person’s voice without modifying the spoken message. It ensures that any information extracted from the transformed voice can hardly be traced back to the original speaker, as validated through state-of-the-art biometric protocols, and it preserves the phonetic information required for human labelling and training of speech-to-text models.
• Release Contributions:
  This version gives access to the 2 generations of tools that have been used to transform the voice, as part of the COMPRISE project (https://www.compriseh2020.eu/). The first one is a python library that implements 2 basic voice conversion methods, both using VLTN. The second one implements an anonymization method using x-vectors and neural waveform models.
• News of the Year:
  We modified the x-vector based transformer by fixing the percentile-based pitch conversion method, using conda in Docker to fix issues with the Python version, and adding data from the speaker pool to simplify quick start.
• URL:
  https://­gitlab.­inria.­fr/­comprise/­voice_transformation
• Contact:
  Marc Tommasi
• Participants:
  Nathalie Vauquier, Brij Mohan Lal Srivastava, Marc Tommasi, Emmanuel Vincent, Md Sahidullah

7.1.2 COMPRISE Weakly Supervised STT

• Name:
  COMPRISE Weakly Supervised Speech-to-Text
• Keywords:
  Speech recognition, Language model, Acoustic Model
• Functional Description:
  COMPRISE Weakly Supervised Speech-to-Text provides two main components for training Speech-to-Text (STT) models. These two components represent the two main approaches proposed in the COMPRISE project, namely (a) semi-supervised training driven by error predictions and (b) weakly supervised training based on utterance level weak labels. These two approaches can be used independently or together. The implementation builds on the Kaldi toolkit. It mainly focuses on obtaining reliable transcriptions of un-transcribed speech data which can be used for training both STT acoustic model (AM) and language model (LM). AM can be any type, although we choose the state-of-the-art TDNN Chain AM in our examples. Statistical n-gram LMs are chosen to support limited data scenarios.
• News of the Year:
  We added a new Confusion Network based Language Model Training (CN2LM) component. In addition, we updated the setup script, and made a few additional fixes to the code and the documentation.
• URL:
  https://­gitlab.­inria.­fr/­comprise/­speech-to-text-weakly-supervised-learning
• Authors:
  Imran Sheikh, Emmanuel Vincent, Irina Illina
• Contact:
  Emmanuel Vincent

7.1.3 Asteroid

• Name:
  Asteroid: The PyTorch-based audio source separation toolkit for researchers.
• Keywords:
  Source Separation, Deep learning
• Functional Description:
  Asteroid is an open-source toolkit made to design, train, evaluate, use and share neural network based audio source separation and speech enhancement models. Inspired by the most successful neural source separation systems, Asteroid provides all neural building blocks required to build such a system. To improve reproducibility, Kaldi-style recipes on common audio source separation datasets are also provided. Experimental results obtained with Asteroid’s recipes show that our implementations are at least on par with most results reported in reference papers.
• News of the Year:
  - Added GEVD beamformer - Added recipe for Multi-Decoder DPRNN - Enable WER evaluation with GPU - Added model and support for voice activity detection
• URL:
  https://­github.­com/­asteroid-team/­asteroid
• Contact:
  Antoine Deleforge
• Participants:
  Manuel Pariente, Mathieu Hu, Joris Cosentino, Sunit Sivasankaran, Mauricio Michel Olvera Zambrano, Fabian Robert Stoter

7.1.4 Web-based Pronunciation Learning Application

• Keywords:
  Pronunciation training, Talking head, Second language learning
• Scientific Description:
  This platform highlights our work on realistic animation of a talking head from speech (also called lipsync). Our lipsync system is operational for German. The evaluation of pronunciation is based on our work on speech recognition. The work on evaluation is not fully completed.
• Functional Description:
  This web-based application is dedicated to foreign language pronunciation learning (current version was developed for the German language). It is intended for high school and middle school students. There are two types of exercises that are integrated in this application. (1) Flashcards: Cards are presented, then a virtual teacher (a 3D talking head) pronounces the words and sentences corresponding to these cards. Students can practice and make an evaluation of their word comprehension. (2) Speech recognition. The application displays a list of words/phrases that the student pronounces and the system gives feedback on the quality of the pronunciation. This application is composed of two modules: one for students (described above) and one for teachers, allowing them to create lessons, and to follow the results and progress of student evaluations.
• News of the Year:
  The flash cards application is quite complete. We have completely developed the student version. The teacher version is well developed. We have completed the administration interface to add/remove a teacher/student/class account. It is planned to have a collaboration with the DANE and the rectorat Nancy-Metz to test the platform with the students of the colleges.
• Contact:
  Slim Ouni
• Participants:
  Theo Biasutto–Lervat, Denis Jouvet, Slim Ouni, Thomas Girod, Leon Rohrbacher

7.1.5 HUMAN

• Name:
  Hierarchical Universal Modular ANnotator
• Keyword:
  Annotation tool
• Scientific Description:
  A lot of real-world phenomena are complex and cannot be captured by single task annotations. This causes a need for subsequent annotations, with interdependent questions and answers describing the nature of the subject at hand. Even in the case a phenomenon is easily captured by a single task, the high specialization of most annotation tools can result in having to switch to another tool if the task only slightly changes. HUMAN is a novel web-based annotation tool that addresses the above problems by a) covering a variety of annotation tasks on both textual and image data, and b) the usage of an internal deterministic state machine, allowing the researcher to chain different annotation tasks in an interdependent manner. Further, the modular nature of the tool makes it easy to define new annotation tasks and integrate machine learning algorithms e.g., for active learning. HUMAN comes with an easy-to-use graphical user interface that simplifies the annotation task and management.
• Functional Description:
  Hierarchical: Supports annotation of hierarchical data. This makes it easy to annotate instances (e.g. online comments) together with their context (e.g. the thread of comments a comment was posted in). Universal: Handles both textual data with and without context as well as PDFs and image annotation. Modular: Various question types (labeling questions, multiple-choice, yes-no, setting bounding boxes etc.) that are self-contained and can be arranged in any order needed. This also makes it easy to implement new custom question types and features. ANnotator: Comes with an easy to use GUI interface for your annotators and project manager.
• News of the Year:
  HUMAN was used for the annotation of the MPHASIS corpus
• URL:
  https://­github.­com/­uds-lsv/­human/
• Publication:
  hal-02958831
• Contact:
  Ashwin D'Sa

8.1.1 Integrating domain knowledge

8.1.2 Learning from little/no labeled data

8.1.3 Preserving privacy

Speech signals convey a lot of private information. To protect speakers, we pursued our investigation of x-vector based voice anonymization. We conducted an extensive study of the impact of four design choices (speaker distance metric, target region of x-vector space, target gender, speaker- or utterance-level target selection) on privacy and utility 84. We have studied the modification of the fundamental frequency to improve consistency with the selected target x-vector, especially in the case of cross gender voice conversion 23, and investigated the behavior of the anonymization process with respect to the selected x-vector target identities under a white-box assessment 24. We have also explored attack scenarios of the voice anonymization system using various techniques of embeddings alignment 25, and evaluated the impact of the voice anonymization process on emotional speech data 49. Finally, we showed that slicing utterances into shorter segments further improves privacy at no cost in utility 81.

In a complementary line of work, we studied the adaptation of ASR language models trained on anonymized text data to the statistics of the original text data 87.

We analyzed the results of the 1st Voice Privacy Challenge which we had organized in 2020 in an article 86 and a detailed technical report 85. We presented a survey of our work in this area at the 1st ISCA Symposium on Security and Privacy in Speech Communication 18.

8.2.1 Articulatory modeling

8.2.2 Multimodal expressive speech

8.2.3 Categorization of sounds and prosody

8.3.1 Acoustic environment analysis

8.3.2 Speech enhancement and noise robustness

8.3.3 Linguistic and semantic processing

9.1.1 Ministère des Armées

• Company: Ministère des Armées (France)
• Duration: Sep 2018 – Aug 2021
• Participants: Raphaël Duroselle, Denis Jouvet, Irène Illina
• Abstract: This contract corresponds to the PhD thesis of Raphaël Duroselle on the application of deep learning techniques for domain adaptation in speech processing.

9.1.2 Facebook

• Company: Facebook AI Research (France)
• Duration: Nov 2018 – Nov 2021
• Participants: Adrien Dufraux, Emmanuel Vincent
• Abstract: This CIFRE contract funds the PhD thesis of Adrien Dufraux. Our goal is to explore cost-effective weakly supervised learning approaches, as an alternative to fully supervised or fully unsupervised learning for automatic speech recognition.

10.1.1 FP7 & H2020 projects

10.1.2 Other european programs/initiatives

PIA2 ISITE LUE

• Title:
  Lorraine Université d’Excellence
• Duration:
  Avr 2016 - Jul 2021
• Coordinator:
  Univ de Lorraine
• Participants:
  Tulika Bose, Dominique Fohr, Irène Illina
• Abstract:
  LUE (Lorraine Université d’Excellence) was designed as an “engine” for the development of excellence, by stimulating an original dialogue between knowledge fields. The IMPACT initiative OLKI (Open Language and Knowledge for Citizens) funds the PhD thesis of Tulika Bose on the detection and classification of hate speech.

E-FRAN METAL

• Title:
  Modèles Et Traces au service de l’Apprentissage des Langues
• Duration:
  Oct 2016 - Dec 2021
• Coordinator:
  Anne Boyer (LORIA, Nancy)
• Partners:
  LORIA, Interpsy, LISEC, ESPE de Lorraine, D@NTE (Univ. Versailles Saint Quentin), Sailendra SAS, ITOP Education, Rectorat.
• Participants:
  Theo Biasutto-Lervat, Anne Bonneau, Vincent Colotte, Dominique Fohr, Denis Jouvet, Slim Ouni
• Abstract:
  METAL aims at improving the learning of languages (written and oral) through development of new tools and analysis of numeric traces associated with students' learning. MULTISPEECH is concerned by oral language learning aspects.

ANR JCJC DiSCogs

• Title:
  Distant speech communication with heterogeneous unconstrained microphone arrays
• Duration:
  Sep 2018 – Aug 2022
• Coordinator:
  Romain Serizel (LORIA, Nancy)
• Participants:
  Louis Delebecque, Nicolas Furnon, Irène Illina, Romain Serizel, Emmanuel Vincent
• Collaborators:
  Télécom ParisTech, 7sensing
• Abstract:
  The objective is to solve fundamental sound processing issues in order to exploit the many devices equipped with microphones that populate our everyday life. The solution proposed is to apply deep learning approaches to recast the problem of synchronizing devices at the signal level as a multi-view learning problem.

ANR DEEP-PRIVACY

• Title:
  Distributed, Personalized, Privacy-Preserving Learning for Speech Processing
• Duration:
  Jan 2019 - Jun 2023
• Coordinator:
  Denis Jouvet (Inria, Nancy)
• Partners:
  MULTISPEECH (Inria Nancy), LIUM (Le Mans), MAGNET (Inria Lille), LIA (Avignon)
• Participants:
  Pierre Champion, Denis Jouvet, Hubert Nourtel, Emmanuel Vincent
• Abstract:
  The objective of the DEEP-PRIVACY project is to elaborate a speech transformation that hides the speaker identity for an easier sharing of speech data for training speech recognition models; and to investigate speaker adaptation and distributed training.

ANR ROBOVOX

• Title:
  Robust Vocal Identification for Mobile Security Robots
• Duration:
  Mar 2019 – Jul 2023
• Coordinator:
  Laboratoire d'informatique d'Avignon (LIA)
• Partners:
  Inria (Nancy), LIA (Avignon), A.I. Mergence (Paris)
• Participants:
  Antoine Deleforge, Sandipana Dowerah, Denis Jouvet, Romain Serizel
• Abstract:
  The aim is to improve speaker recognition robustness for a security robot in real environment. Several aspects will be particularly considered such as ambiant noise, reverberation and short speech utterances.

ANR BENEPHIDIRE

• Title:
  Stuttering: Neurology, Phonetics, Computer Science for Diagnosis and Rehabilitation
• Duration:
  Mar 2019 - Fev 2023
• Coordinator:
  Praxiling (Toulouse)
• Partners:
  Praxiling (Toulouse), LORIA (Nancy), INM (Toulouse), LiLPa (Strasbourg).
• Participants:
  Yves Laprie, Slim Ouni, Shakeel Ahmad Sheikh
• Abstract:
  The BENEPHIDIRE project brings together neurologists, speech-language pathologists, phoneticians, and computer scientists specializing in speech processing to investigate stuttering as a speech impairment and to develop techniques for diagnosis and rehabilitation.

ANR LEAUDS

• Title:
  Learning to understand audio scenes
• Duration:
  Apr 2019 - Mar 2023
• Coordinator:
  Université de Rouen Normandie
• Partners:
  Université de Rouen Normandie, Inria (Nancy), Netatmo (Paris)
• Participants:
  Felix Gontier, Mauricio Michel Olvera Zambrano, Romain Serizel, Emmanuel Vincent, and Christophe Cerisara (CNRS - LORIA)
• Abstract:
  LEAUDS aims to make a leap towards developing machines that understand audio input through breakthroughs in the detection of audio events from little annotated data, the robustness to “out-of-the lab” conditions, and language-based description of audio scenes. MULTISPEECH is responsible for research on robustness and for bringing expertise on natural language generation.

Inria Project Lab HyAIAI

• Title:
  Hybrid Approaches for Interpretable AI
• Duration:
  Sep 2019 - Aug 2023
• Coordinator:
  Inria LACODAM (Rennes)
• Partners:
  Inria TAU (Saclay), SEQUEL, MAGNET (Lille), MULTISPEECH, ORPAILLEUR (Nancy)
• Participants:
  Irène Illina, Emmanuel Vincent, Georgios Zervakis
• Abstract:
  HyAIAI is about the design of novel, interpretable artificial intelligence methods based on hybrid approaches that combine state of the art numeric models with explainable symbolic models.

ANR Flash Open Science HARPOCRATES

• Title:
  Open data, tools and challenges for speaker anonymization
• Duration:
  Oct 2019 - Sep 2021
• Coordinator:
  Eurecom (Nice)
• Partners:
  Eurecom (Nice), Inria (Nancy), LIA (Avignon)
• Participants:
  Denis Jouvet, Md Sahidullah, Emmanuel Vincent
• Abstract:
  HARPOCRATES supported the organization of the 1st VoicePrivacy Challenge, including data preparation and baseline software development.

ANR HAIKUS

• Title:
  Artificial Intelligence applied to augmented acoustic Scenes
• Duration:
  Dec 2019 - Nov 2023
• Coordinator:
  Ircam (Paris)
• Partners:
  Ircam (Paris), Inria (Nancy), IJLRA (Paris)
• Participants:
  Antoine Deleforge, Prerak Srivastava, Emmanuel Vincent
• Abstract:
  HAIKUS aims to achieve seamless integration of computer-generated immersive audio content into augmented reality (AR) systems. One of the main challenges is the rendering of virtual auditory objects in the presence of source movements, listener movements and/or changing acoustic conditions.

ANR JCJC DENISE

• Title:
  Tackling hard problems in audio using Data-Efficient Non-linear InverSe mEthods
• Duration:
  Oct 2020 – Sep 2024
• Coordinator:
  Antoine Deleforge (Inria, Nancy)
• Participants:
  Antoine Deleforge, Tom Sprunck
• Collaborators:
  UMR AE, Institut de Recherche Mathématiques Avancées de Strasbourg, Institut de Mathématiques de Bordeaux
• Abstract:
  DENISE aims to explore the applicability of recent breakthroughs in the field of nonlinear inverse problems to audio signal reparation and to room acoustics, and to combine them with compact machine learning models to yield data-efficient techniques.

Action Exploratoire Inria Acoust.IA

• Title:
  Acoust.IA: l'Intelligence Artificielle au Service de l'Acoustique du Bâtiment
• Duration:
  Oct 2020 - Sep 2023
• Coordinator:
  Antoine Deleforge
• Participants:
  Antoine Deleforge, Stéphane Dilungana, and Cédric Foy (CEREMA)
• Abstract:
  This project aims at radically simplifying and improving the acoustic diagnosis of rooms and buildings using new techniques combining machine learning, signal processing and physics-based modeling.

InriaHub ADT PEGASUS

• Title:
  PEGASUS: rehaussement de la ParolE Généralisé par Apprentissage SUperviSé
• Duration:
  Nov 2020 - Oct 2022
• Coordinator:
  Antoine Deleforge
• Participants:
  Joris Cosentino, Antoine Deleforge, Manuel Pariente, Emmanuel Vincent
• Abstract:
  This engineering project aims at further developing, expanding and transfering the Asteroid speech enhancement and separation toolkit recently released by the team 92.

ANR Full3DTalkingHead

• Title:
  Synthèse articulatoire phonétique
• Duration:
  Apr 2021 - Sep 2024
• Coordinator:
  Yves Laprie (LORIA, Nancy)
• Partners:
  LORIA (Nancy), Gipsa-Lab (Grenoble), IADI (Nancy), LPP (Paris)
• Participants:
  Slim Ouni, Vinicius Ribeiro, Yves Laprie
• Abstract:
  The objective is to realize a complete three-dimensional digital talking head including the vocal tract from the vocal folds to the lips, the face and integrating the digital simulation of the aero-acoustic phenomena.

11.1.1 Scientific events: organisation

11.1.2 Scientific events: selection

11.1.3 Journal

11.1.4 Invited talks

• Journée SdL (Sciences du Langage), Universiy of Lorraine, Nancy, April 2021 (S. Ouni)
• Intelligent Sensing Winter School, Queen Mary's University of London, December 2021 (A. Deleforge)

11.1.5 Leadership within the scientific community

• Member of the Steering Committee of ISCA’s Special Interest Group on Security and Privacy in Speech Communication (E. Vincent).
• Member of DCASE steering group (R. Serizel)
• Member of IEEE acoustic and audio signal processing technical committee (A. Deleforge, R. Serizel)
• Secretary/Treasurer, executive member of AVISA (Auditory-VIsual Speech Association), an ISCA Special Interest Group (S. Ouni)
• Vice-president of AFCP - Association Francophone de la Communication Parlée (S. Ouni)

11.1.6 Scientific expertise

• Expertise for Bpifrance on a DeepTech startup funding request (A. Deleforge)
• Member of ANR Evaluation Committee 23 on Artificial Intelligence (E. Vincent)
• Member of ANR Evaluation Committe for ASTRID projects (D. Jouvet)
• Member of the Advisory Board of H2020 FVLLMONTI (E. Vincent)
• Member of the Scientific Committee of an Institute for deaf people, INJS-Metz (A. Piquard-Kipffer)
• Member of the hiring committee for Inria Senior Research Scientists (E. Vincent)
• Member of the hiring committee for a Professor, Avignon Université (D. Jouvet)
• Member of the hiring committee for Junior Research Scientists, Inria Lille - Nord Europe (E. Vincent)
• Member of the hiring committee for a CPPI Europe, Inria Nancy - Grand Est (E. Vincent)
• Member of the hiring committee for a permanent research engineer, Inria Nancy - Grand Est (E. Vincent)
• Member of the hiring committee for an Assistant Professor, Le Mans Université (D. Jouvet)
• Reviewer of ANR projects (D. Jouvet, Y. Laprie)
• Reviewer of CIFRE thesis proposal (D. Jouvet, S. Ouni)
• Reviewer of ERC projects (Y. Laprie)
• Reviewer of projects for Czech Science Foundation (I. Illina, D. Jouvet)
• Reviewer of projects for Austrian Academy of Sciences (I. Illina)

11.1.7 Research administration

• Head of the AM2I Scientific Pole of Université de Lorraine (Y. Laprie)
• Deputy Head of Science of Inria Nancy - Grand Est (E. Vincent)
• Scientific Director for the partnership between Inria and DFKI (E. Vincent)
• President of the Commission Locale de Développement Durable (CLDD) of Inria Nancy (A. Deleforge)
• Member of Management board of Université de Lorraine (Y. Laprie)
• Member of the CNU 27 (Conseil National des Universités) - Computer Science (S. Ouni)
• Member of Inria’s Evaluation Committee (E. Vincent)
• Member of the Comité Espace Transfert of Inria Nancy - Grand Est (E. Vincent)
• Member of the commission for the scientific staff (COMIPERS) of the research center Inria Nancy - Grand Est (R. Serizel)
• Member of the commission for the technological developpment (CDT) of the research center Inria Nancy (R. Serizel)
• Member of Commission paritaire of Université de Lorraine (Y. Laprie)
• Member of the Commission Locale de Développement Durable (CLDD) of Inria Nancy (D. Fohr)
• Member of the Commission des Utilisateurs des Moyens Informatiques (CUMI) of Inria Nancy (D. Fohr)
• Member of the Conseil de la Fédération Charles Hermite (I. Illina)
• Member of the Commission de Sélection ATER (IUT Charlemagne) (I. Illina)

11.2.1 Teaching

• DUT: I. Illina, Java programming (100 hours), Linux programming (58 hours), and Advanced Java programming (40 hours), L1, University of Lorraine, France
• DUT: I. Illina, Supervision of student projects and internships (50 hours), L2, University of Lorraine, France
• DUT: R. Serizel, Introduction to office tools (108 hours), Multimedia and web (20 hours), Documents and databases (20 hours), L1, University of Lorraine, France
• DUT: R. Serizel, Multimedia content and indexing (14 hours), Content indexing and retrieval software (20 hours), L2, University of Lorraine, France
• DUT: S. Ouni, Programming in Java (24 hours), Web Programming (24 hours), Graphical User Interface (96 hours), L1, University of Lorraine, France
• DUT: S. Ouni, Advanced Algorihms (24 hours), L2, University of Lorraine, France
• Licence: A. Bonneau, Phonetics (17 hours), L2, École d’audioprothèse, University of Lorraine, France
• Licence: V. Colotte, Digital literacy and tools (hybrid courses, 50 hours), L1, University of Lorraine, France
• Licence: V. Colotte, System (35 hours), L3, University of Lorraine, France
• Licence: A. Piquard-Kipffer, Education Science (32 hours), L1, Département d'orthophonie, University of Lorraine, France
• Licence: A. Piquard-Kipffer, Learning to Read (34 hours), L2, Département d'orthophonie, University of Lorraine, France
• Licence: A. Piquard-Kipffer, Psycholinguistics (20 hours), Departement Orthophonie, University Pierre et Marie Curie, Paris, France
• Licence: A. Piquard-Kipffer, Dyslexia, Dysorthographia (12 hours), L3, Département d'orthophonie, University of Lorraine, France
• Licence: A. Piquard-Kipffer, Mathematics Didactics, 9 hours, L3, Departement Orthophonie, University of Lorraine, France
• Licence and Master: A. Deleforge, Introduction to Machine Learning, 12 hours L3, 12 hours M1, Télécom Physique Strasbourg, France
• Master: V. Colotte, Integration project: multimodal interaction with Pepper Robot (15 hours), M2, University of Lorraine, France
• Master: D. Jouvet and S. Ouni, Multimodal oral comunication (24 hours), M2, University of Lorraine, France
• Master: Y. Laprie, Speech corpora (30 hours), M1, University of Lorraine, France
• Master: S. Ouni, Multimedia in Distributed Information Systems (31 hours), M2, University of Lorraine, France
• Master: A. Piquard-Kipffer, Dyslexia, Dysorthographia diagnosis (6 hours), Deaf people & reading (21 hours), M1, Département d'orthophonie, University of Lorraine, France
• Master: A. Piquard-Kipffer, French Language Didactics (53 hours), M2, INSPE University of Lorraine, France
• Master: A. Piquard-Kipffer, Psychology (6 hours), M2, Departement of Psychology, University of Lorraine, France
• Executive Master : A. Piquard-Kipffer, Psychology, 12 hours, M2, Special Educational Needs with University of Lorraine, INSPÉ & UIR, International University of Rabat (Morocco)
• Master: R. Serizel, S. Ouni, P. Magron and V. Ribeiro, Oral speech processing (24 hours), M2, University of Lorraine
• Master: E. Vincent, A. Kulkarni and P. Magron, Neural networks (38 hours), M2, University of Lorraine
• Continuous training: A. Piquard-Kipffer, Special Educational Needs (53 hours), INSPE,University of Lorraine, France
• Continuous training: E. Vincent, Neural networks (14 hours), Data Scientist curriculum, University of Lorraine
• PhD: A. Piquard-Kipffer, Language Pathology (20 hours), EHESP, University of Sorbonne, Paris, France
• Other: V. Colotte, Co-Responsible for NUMOC (Digital literacy by hybrid courses) for the University of Lorraine, France (for 7000 students)
• Other: S. Ouni, Responsible of Année Spéciale DUT, University of Lorraine

11.2.2 Supervision

• PhD: Théo Biasutto-Lervat, “Modélisation de la coarticulation multimodale : vers l’animation d’une tête parlante intelligible”, Jan 29, 2021, S. Ouni 73
• PhD: Lou Lee, “Fonctions pragmatiques et prosodie de marqueurs discursifs en français et en anglais”, Apr 6, 2021, Y. Keromnes (ATILF) and D. Jouvet
• PhD: Nicolas Turpault, “Analyse des problématiques liées à la reconnaissance de sons ambiants en environnement réel”, May 31, 2021, R. Serizel and E. Vincent 77
• PhD: Manuel Pariente, “Deep learning-based phase-aware audio signal modeling and estimation”, Sep 29, 2021, A. Deleforge and E. Vincent 75
• PhD: Raphaël Duroselle, “Robustesse au canal des systèmes de reconnaissance de la langue”, Oct 28, 2021, D. Jouvet and I. Illina 74
• PhD: Brij Mohan Lal Srivastava, “Speaker anonymization — Representation, evaluation and formal guarantees”, Dec 2, 2021, M. Tommasi (MAGNET project-team), E. Vincent and A. Bellet (MAGNET project-team) 76
• PhD: Nicolas Furnon, “Deep-learning based speech enhancement with ad-hoc microphone arrays”, Dec 14, 2021, R. Serizel, I. Illina and S. Essid (Télécom ParisTech)

• PhD in progress: Ajinkya Kulkarni, “Expressive speech synthesis by deep learning”, Oct. 2018, V. Colotte and D. Jouvet
• PhD in progress: Adrien Dufraux, “Leveraging noisy, incomplete, or implicit labels for automatic speech recognition”, Nov 2018, E. Vincent, A. Brun (LORIA) and M. Douze (Facebook AI Research)
• PhD in progress: Ashwin Geet D'Sa, “Natural Language Processing: Online hate speech against migrants”, Apr 2019, I. Illina and D. Fohr
• PhD in progress: Tulika Bose, “Online hate speech and topic classification”, Sep 2019, I. Illina, D. Fohr and A. Monnier (CREM)
• PhD in progress: Mauricio Michel Olvera Zambrano, “Robust audio event detection”, Oct 2019, E. Vincent and G. Gasso (LITIS)
• PhD in progress: Pierre Champion, “Privacy preserving and personalized transformations for speech recognition”, Oct 2019, D. Jouvet and A. Larcher (LIUM)
• PhD in progress: Shakeel Ahmad Sheikh, “Identifying disfluency in speakers with stuttering, and its rehabilitation, using DNN”, Oct 2019, S. Ouni
• PhD in progress: Sandipana Dowerah, “Robust speaker verification from far-field speech”, Oct 2019, D. Jouvet and R. Serizel
• PhD in progress: Georgios Zervakis, “Integration of symbolic knowledge into deep learning”, Nov 2019, M. Couceiro (LORIA) and E. Vincent
• PhD in progress: Nicolas Zampieri, “Automatic classification using deep learning of hate speech posted on the Internet”, Nov. 2019, I. Illina and D. Fohr
• PhD in progress: Xuechen Liu, “Robust speaker recognition for smart assistant technology”, Jan 2020, M. Sahidullah
• PhD in progress: Prerak Srivastava, “Hearing the walls of a room: machine learning for audio augmented reality”, Oct 2020, A. Deleforge and E. Vincent
• PhD in progress: Stéphane Dilungana, “L’intelligence artificielle au service du diagnostic acoustique : Apprendre à entendre les parois d’une salle”, Oct 2020, A. Deleforge, C. Foy (UMR AE) and S. Faisan (iCube)
• PhD in progress: Vinicius Souza Ribeiro, “Tracking articulatory contours in MR images and prediction of the vocal tract shape from a sequence of phonemes to be articulated”, Oct 2020, Y. Laprie
• PhD in progress: François Effa, “Détection d'alarmes dans le bruit”, Jan 2021, R. Serizel, J.-P. Arz (INRS), N. Grimault (Centre de Recherche en Neurosciences de Lyon)
• PhD in progress: Seyed Ahmad Hosseini, “3D sign language generation”, Feb 2021, S. Ouni and M. Sadeghi
• PhD in progress: Louis Abel, “Expressive audio-visual speech synthesis in an interaction context”, Oct 2021, S. Ouni and V. Colotte
• PhD in progress: Can Cui, “Séparation, diarisation et reconnaissance automatique de la parole conjointes et embarquées pour la génération de comptes-rendus de réunions”, Oct 2021, M. Sadeghi and E. Vincent
• PhD in progress: Sewade Olaolu Ogun, “Multi-factor data augmentation and transfer learning for embedded automatic speech recognition”, Oct 2021, V. Colotte and E. Vincent
• PhD in progress: Tom Sprunck, “Hearing the Shape of a Room: Towards Acoustic Super-resolution”, Nov 2021, A. Deleforge, C. Foy (UMR AE) and Y. Privat (Univ. Strasbourg)
• PhD in progress: Mickaëlla Grondin, “Modeling gestures and speech in interactions”, Nov 2021, S. Ouni and F. Hirsch (Praxiling)

11.2.3 Juries

11.3.1 Articles and contents

• Article “Enabling voice-based apps with European values”, ERCIM News, Jul 2021 (A. Campbell, E. Vincent) 89
• Interview for “Dresseur d’intelligence artificielle, métier de demain ?”, WE DEMAIN, Nov 2021 (E. Vincent)
• Podcast “COMPRISE, the privacy-friendly, inclusive voice interface”, podcast, Dec 2021 (E. Vincent)
• After its publication, the scientific paper "Impact of lip-reading on speech perception in French-speaking children at-risk for reading failure assessed from age 5 to 7." by A. Piquard-Kipffer et al. 15 has been mentionned and commented on several web sites (Ministère de l'Enseignement Supérieur, de la Recherche et de l'Innovation, CNRS, Université de Lorraine, LORIA, CNRS - le journal, YouTube, SoundCloud(CNRS)), social networks (twitter) and journals (L'Express, Le Figaro, revue Cerveau & Psycho)

11.3.2 Interventions

• Chiche, Lycée Chopin, Nancy, Nov 2021 (R. Serizel)
• Chiche, Lycée Saint-Pierre Chanel, Thionville (2 classes), Dec 2021 (E. Vincent)
• Theater play "Drone Control" by Les Sens des Mots, written by Charlotte Lagrange, inspired by the research work of A. Deleforge, played 4 times in 2021 in front of general audiences (approx. 200 spectators in total)

International journals

• 6 articleZ.Zaineb Chelly Dagdia and C.Christine Zarges. A detailed study of the distributed rough set based locality sensitive hashing feature selection technique.Fundamenta Informaticae1822September 2021, 111-179
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• 7 articleS.Samuele Cornell, M.Maurizio Omologo, S.Stefano Squartini and E.Emmanuel Vincent. Overlapped speech detection and speaker counting using distant microphone arrays.Computer Speech and Language72October 2021
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• 8 articleS.Sara Dahmani, V.Vincent Colotte, V.Valérian Girard and S.Slim Ouni. Learning emotions latent representation with CVAE for Text-Driven Expressive AudioVisual Speech Synthesis.Neural Networks1412021, 315-329
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• 9 articleC.Cédric Foy, A.Antoine Deleforge and D.Diego Di Carlo. Mean absorption estimation from room impulse responses using virtually supervised learning.Journal of the Acoustical Society of America1502January 2021, 1286-1299
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• 10 articleN.Nicolas Furnon, R.Romain Serizel, S.Slim Essid and I.Irina Illina. DNN-based mask estimation for distributed speech enhancement in spatially unconstrained microphone arrays.IEEE/ACM Transactions on Audio, Speech and Language Processing292021, 2310 - 2323
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• 11 articleK.Karyna Isaieva, Y.Yves Laprie, J.Justine Leclère, I. K.Ioannis K Douros, J.Jacques Felblinger and P.-A.Pierre-André Vuissoz. Multimodal dataset of real-time 2D and static 3D MRI of healthy French speakers.Scientific Data 81October 2021, 258
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• 12 articleK. A.Kishore A. Kumar, D.Dipjyoti Paul, M.Monisankha Pal, M.Md Sahidullah and G.Goutam Saha. Speech Frame Selection for Spoofing Detection with an Application to Partially Spoofed Audio-Data.International Journal of Speech TechnologyJanuary 2021
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• 13 articleX.Xuechen Liu, M.Md Sahidullah and T.Tomi Kinnunen. Optimizing Multi-Taper Features for Deep Speaker Verification.IEEE Signal Processing Letters282021, 2187 - 2191
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• 14 articleA.Andreas Nautsch, X.Xin Wang, N.Nicholas Evans, T.Tomi Kinnunen, V.Ville Vestman, M.Massimiliano Todisco, H.Hector Delgado, M.Md Sahidullah, J.Junichi Yamagishi and K. A.Kong Aik Lee. ASVspoof 2019: Spoofing Countermeasures for the Detection of Synthesized, Converted and Replayed Speech.IEEE Transactions on Biometrics, Behavior, and Identity Science32February 2021, 252-265
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• 15 articleA.Agnès Piquard-Kipffer, T.Thalia Cavadini, L.Liliane Sprenger-Charolles and E.Edouard Gentaz. Impact of lip-reading on speech perception in French-speaking children at risk for reading failure assessed from age 5 to 7.Annee Psychologique121June 2021, 3-18
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• 16 articleM.Mostafa Sadeghi and X.Xavier Alameda-Pineda. Mixture of Inference Networks for VAE-based Audio-visual Speech Enhancement.IEEE Transactions on Signal Processing69March 2021, 1899-1909
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• 17 articleN.Nirmalya Sen, M.Md Sahidullah, H.Hemant Patil, S. K.Shyamal Kumar Das Mandal, S. K.Sreenivasa Krothapalli Rao and T. K.Tapan Kumar Basu. Utterance partitioning for speaker recognition: an experimental review and analysis with new findings under GMM-SVM framework.International Journal of Speech Technology24December 2021, 1067–1088
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International peer-reviewed conferences

• 18 inproceedingsJ.-F.Jean-Francois Bonastre, H.Hector Delgado, N.Nicholas Evans, T.Tomi Kinnunen, K. A.Kong Aik Lee, X.Xuechen Liu, A.Andreas Nautsch, P.-G.Paul-Gauthier Noe, J.Jose Patino, M.Md Sahidullah, B. M.Brij Mohan Lal Srivastava, M.Massimiliano Todisco, N.Natalia Tomashenko, E.Emmanuel Vincent, X.Xin Wang and J.Junichi Yamagishi. Benchmarking and challenges in security and privacy for voice biometrics.SPSC 2021 - 1st ISCA Symposium on Security and Privacy in Speech CommunicationMagdeburg, GermanyNovember 2021
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• 19 inproceedingsA.Anne Bonneau. Voicing assimilations by French Speakers of German in stop-fricative sequences.INTERSPEECH 2021Brno, Czech RepublicAugust 2021
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• 20 inproceedingsT.Tulika Bose, I.Irina Illina and D.Dominique Fohr. Generalisability of Topic Models in Cross-corpora Abusive Language Detection.NLP4IF 2021 - Workshop Censorship, Disinformation, and PropagandaMexico city/Virtual, MexicoJune 2021
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• 21 inproceedingsT.Tulika Bose, I.Irina Illina and D.Dominique Fohr. Unsupervised Domain Adaptation in Cross-corpora Abusive Language Detection.SocialNLP 2021 - The 9th International Workshop on Natural Language Processing for Social MediaVirtual, FranceJune 2021
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• 22 inproceedingsE.Eduardo Calò, L.Léo Jacqmin, T.Thibo Rosemplatt, M.Maxime Amblard, M.Miguel Couceiro and A.Ajinkya Kulkarni. GECko+: a Grammatical and Discourse Error Correction Tool.Actes de la 28e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 3 : DémonstrationsTALN 2021 - 28e Conférence sur le Traitement Automatique des Langues NaturellesLille / Virtual, FranceATALA2021, 8-11
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• 23 inproceedingsP.Pierre Champion, D.Denis Jouvet and A.Anthony Larcher. A Study of F0 Modification for X-Vector Based Speech Pseudonymization Across Gender.PPAI 2021 - 2nd AAAI Workshop on Privacy-Preserving Artificial IntelligenceVirtual, ChinaNovember 2020
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• 24 inproceedingsP.Pierre Champion, D.Denis Jouvet and A.Anthony Larcher. Evaluating X-vector-based Speaker Anonymization under White-box Assessment.SPECOM 2021 - 23rd International Conference on Speech and ComputerSaint Petersburg, RussiaSeptember 2021
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• 25 inproceedingsP.Pierre Champion, T.Thomas Thebaud, G.Gaël Le Lan, A.Anthony Larcher and D.Denis Jouvet. On the invertibility of a voice privacy system using embedding alignement.ASRU 2021 - IEEE Automatic Speech Recognition and Understanding WorkshopCartagena, ColombiaDecember 2021
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• 26 inproceedingsB.Bhusan Chettri, R. G.Rosa González Hautamäki, M.Md Sahidullah and T.Tomi Kinnunen. Data Quality as Predictor of Voice Anti-Spoofing Generalization.INTERSPEECH 2021Brno, Czech RepublicAugust 2021
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• 27 inproceedingsS.Spandan Dey, G.Goutam Saha and M.Md Sahidullah. Cross-Corpora Language Recognition: A Preliminary Investigation with Indian Languages.EUSIPCO 2021 - 29th European Signal Processing ConferenceDublin / Virtual, IrelandAugust 2021
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• 28 inproceedingsI. K.Ioannis K Douros, A.Ajinkya Kulkarni, Y.Yu Xie, C.Chrysanthi Dourou, J.Jacques Felblinger, K.Karyna Isaieva, P.-A.Pierre-André Vuissoz and Y.Yves Laprie. MRI Vocal Tract Sagittal Slices Estimation during Speech Production of CV.EUSIPCO 2020 - 28th European Signal Processing ConferenceAmsterdam / Virtual, NetherlandsJanuary 2021
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• 29 inproceedingsR.Raphaël Duroselle, M.Md Sahidullah, D.Denis Jouvet and I.Irina Illina. Language recognition on unknown conditions: the LORIA-Inria-MULTISPEECH system for AP20-OLR Challenge.INTERSPEECH 2021Brno, Czech RepublicAugust 2021
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• 30 inproceedingsR.Raphaël Duroselle, M.Md Sahidullah, D.Denis Jouvet and I.Irina Illina. Modeling and training strategies for language recognition systems.INTERSPEECH 2021Brno, Czech RepublicAugust 2021
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• 31 inproceedingsG.Giacomo Ferroni, N.Nicolas Turpault, J.Juan Azcarreta, F.Francesco Tuveri, R.Romain Serizel, Ç.Çagdaş Bilen and S.Sacha Krstulović. Improving Sound Event Detection Metrics: Insights from DCASE 2020.ICASSP 2021 - 46th International Conference on Acoustics, Speech, and Signal ProcessingToronto/Virtual, CanadaJune 2021
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• 32 inproceedingsD.Dominique Fohr and I.Irina Illina. BERT-based Semantic Model for Rescoring N-best Speech Recognition List.INTERSPEECH 2021Proceedings of INTERSPEECH 2021Brno, Czech RepublicAugust 2021
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• 33 inproceedingsN.Nicolas Furnon, R.Romain Serizel, S.Slim Essid and I.Irina Illina. Attention-based distributed speech enhancement for unconstrained microphone arrays with varying number of nodes.European Signal Processing Conference (EUSIPCO)EUSIPCO 2021 - 29th European Signal Processing ConferenceDublin / Virtual, IrelandAugust 2021
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• 34 inproceedingsN.Nicolas Furnon, R.Romain Serizel, I.Irina Illina and S.Slim Essid. Distributed speech separation in spatially unconstrained microphone arrays.ICASSP 2021 - 46th International Conference on Acoustics, Speech, and Signal ProcessingToronto / Virtual, CanadaJune 2021
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• 35 inproceedingsA.Ashwin Geet D'Sa, I.Irina Illina, D.Dominique Fohr, D.Dietrich Klakow and D.Dana Ruiter. Exploring Conditional Language Model Based Data Augmentation Approaches For Hate Speech Classification.TSD 2021 - 24th International Conference on Text, Speech and DialogueOlomouc, Czech RepublicSeptember 2021
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• 36 inproceedingsF.Félix Gontier, R.Romain Serizel and C.Christophe Cerisara. Automated audio captioning by fine-tuning bart with audioset tags.DCASE 2021 - 6th Workshop on Detection and Classification of Acoustic Scenes and EventsVirtual, SpainNovember 2021
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• 37 inproceedingsP.-A.Pierre-Amaury Grumiaux, S.Srdan Kitić, P.Prerak Srivastava, L.Laurent Girin and A.Alexandre Guérin. Saladnet: Self-Attentive Multisource Localization in the Ambisonics Domain.WASPAA 2021 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)WASPAA 2021 - IEEE Workshop on Applications of Signal Processing to Audio and AcousticsNew Paltz / Virtual, United StatesIEEEOctober 2021, 336-340
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• 38 inproceedingsI.Irina Illina and D.Dominique Fohr. DNN-based semantic rescoring models for speech recognition.TSD 2021 - 24th International Conference on Text, Speech and Dialogueproceedings of TSD 2021Olomouc, Czech RepublicSeptember 2021
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• 39 inproceedingsO.Olivia Janin and A.Agnès Piquard-Kipffer. De codes gestuo-manuels à la Langue des Signes Française : usages et enjeux à la maternelle dans le cadre des gestes professionnels inclusifs et des adaptations didactiques.IDEKI 2021 - 4ème colloque international Didactiques et métiers de l'humainPont-A-Mousson, FranceDecember 2021
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• 40 inproceedingsZ.Zhiqi Kang, R.Radu Horaud and M.Mostafa Sadeghi. Robust Face Frontalization For Visual Speech Recognition.ICCVW 2021 - International Conference on Computer Vision WorkshopsMontreal - Virtual, CanadaIEEEOctober 2021, 2485-2495
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• 41 inproceedingsT.Tomi Kinnunen, A.Andreas Nautsch, M.Md Sahidullah, N.Nicholas Evans, X.Xin Wang, M.Massimiliano Todisco, H.Héctor Delgado, J.Junichi Yamagishi and L.Lee Kong Aik. Visualizing Classifier Adjacency Relations: A Case Study in Speaker Verification and Voice Anti-Spoofing.INTERSPEECH 2021Brno, Czech RepublicAugust 2021
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• 42 inproceedingsA.Ajinkya Kulkarni, V.Vincent Colotte and D.Denis Jouvet. Improving transfer of expressivity for end-to-end multispeaker text-to-speech synthesis.EUSIPCO 2021 - 29th European Signal Processing ConferenceDublin / Virtual, IrelandAugust 2021
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• 43 inproceedings M.Manuel Leitao, E.Elodie Venti, T.Thomas Sigiez, C.Christophe Laroche, M.Marie Perini and A.Agnès Piquard-Kipffer. Projet LogilecSur : quelles stratégies enseignantes pour guider des élèves sourds vers l'autonomie en compréhension écrite ? IDEKI 2021 - 4ème colloque international Didactiques et métiers de l'humain Pont-à-Mousson, France December 2021
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• 44 inproceedingsX.Xuechen Liu, M.Md Sahidullah and T.Tomi Kinnunen. Learnable MFCCs for Speaker Verification.ISCAS 2021 - IEEE International Symposium on Circuits and SystemsDaegu, South KoreaMay 2021
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• 45 inproceedingsX.Xuechen Liu, M.Md Sahidullah and T.Tomi Kinnunen. Optimized Power Normalized Cepstral Coefficients Towards Robust Deep Speaker Verification.ASRU 2021 - IEEE Automatic Speech Recognition and Understanding WorkshopCartagena, ColombiaDecember 2021
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• 46 inproceedingsX.Xuechen Liu, M.Md Sahidullah and T.Tomi Kinnunen. Parameterized Channel Normalization for Far-field Deep Speaker Verification.ASRU 2021 - IEEE Automatic Speech Recognition and Understanding WorkshopCartagena, ColombiaDecember 2021
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• 47 inproceedingsM.Mohammad Mohammadamini, D.Driss Matrouf, J.-F.Jean-Francois Bonastre, R.Romain Serizel, S.Sandipana Dowerah and D.Denis Jouvet. Compensate multiple distortions for speaker recognition systems.EUSIPCO 2021 - 29th European Signal Processing ConferenceDublin / Virtual, IrelandAugust 2021
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• 48 inproceedingsV.-N.Viet-Nhat Nguyen, M.Mostafa Sadeghi, E.Elisa Ricci and X.Xavier Alameda-Pineda. Deep Variational Generative Models for Audio-visual Speech Separation.MLSP 2021 - IEEE International Workshop on Machine Learning for Signal ProcessingGold Coast, AustraliaOctober 2021
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• 49 inproceedingsH.Hubert Nourtel, P.Pierre Champion, D.Denis Jouvet, A.Anthony Larcher and M.Marie Tahon. Evaluation of Speaker Anonymization on Emotional Speech.SPSC 2021 - 1st ISCA Symposium on Security and Privacy in Speech CommunicationVirtual, GermanyNovember 2021
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• 50 inproceedingsM.Michel Olvera, E.Emmanuel Vincent and G.Gilles Gasso. Improving Sound Event Detection with Auxiliary Foreground-Background Classification and Domain Adaptation.DCASE 2021 - 6th Workshop on Detection and Classification of Acoustic Scenes and EventsVirtual, SpainNovember 2021
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• 51 inproceedingsM.Michel Olvera, E.Emmanuel Vincent, R.Romain Serizel and G.Gilles Gasso. Foreground-Background Ambient Sound Scene Separation.EUSIPCO 2020 - 28th European Signal Processing ConferenceAmsterdam / Virtual, NetherlandsJanuary 2021
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• 52 inproceedingsV.Vinicius Ribeiro, K.Karyna Isaieva, J.Justine Leclère, P.-A.Pierre-André Vuissoz and Y.Yves Laprie. Towards the prediction of the vocal tract shape from the sequence of phonemes to be articulated.INTERSPEECH 2021Brno, Czech RepublicAugust 2021
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• 53 inproceedingsF.Francesca Ronchini, R.Romain Serizel, N.Nicolas Turpault and S.Samuele Cornell. The impact of non-target events in synthetic soundscapes for sound event detection.DCASE 2021 - Detection and Classification of Acoustic Scenes and EventsBarcelona/Virtual, SpainNovember 2021
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• 54 inproceedingsM.Mostafa Sadeghi and X.Xavier Alameda-Pineda. Switching Variational Auto-Encoders for Noise-Agnostic Audio-visual Speech Enhancement.ICASSP 2021 - 46th International Conference on Acoustics, Speech, and Signal ProcessingToronto / Virtual, CanadaIEEEJune 2021, 1-5
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• 55 inproceedingsM.Md Sahidullah, A.Achintya Kumar Sarkar, V.Ville Vestman, X.Xuechen Liu, R.Romain Serizel, T.Tomi Kinnunen, Z.-H.Zheng-Hua Tan and E.Emmanuel Vincent. UIAI System for Short-Duration Speaker Verification Challenge 2020.SLT 2021 - IEEE Spoken Language Technology WorkshopShenzhen / Virtual, ChinaShort-duration Speaker Verification Challenge 2020January 2021
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• 56 inproceedingsU.Usama Saqib, A.Antoine Deleforge and J. R.Jesper Rindom Jensen. Detecting acoustic reflectors using a robot's ego-noise.IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)ICASSP 2021 - 46th International Conference on Acoustics, Speech, and Signal ProcessingToronto / Virtual, CanadaJune 2021
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• 57 inproceedingsS. A.Shakeel Ahmad Sheikh, M.Md Sahidullah, F.Fabrice Hirsch and S.Slim Ouni. StutterNet: Stuttering Detection Using Time Delay Neural Network.EUSIPCO 2021 - 29th European Signal Processing ConferenceDublin / Virtual, IrelandAugust 2021
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• 58 inproceedingsP.Premjeet Singh, G.Goutam Saha and M.Md Sahidullah. Deep scattering network for speech emotion recognition.EUSIPCO 2021 - 29th European Signal Processing ConferenceDublin / Virtual, IrelandAugust 2021
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• 59 inproceedingsP.Premjeet Singh, G.Goutam Saha and M.Md Sahidullah. Non-linear frequency warping using constant-Q transformation for speech emotion recognition.ICCCI 2021 - International Conference on Computer Communication and InformaticsCoimbatore, IndiaJanuary 2021
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• 60 inproceedingsS.Sunit Sivasankaran, E.Emmanuel Vincent and D.Dominique Fohr. Analyzing the impact of speaker localization errors on speech separation for automatic speech recognition.EUSIPCO 2020 - 28th European Signal Processing ConferenceAmsterdam / Virtual, NetherlandsJanuary 2021
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• 61 inproceedingsS.Sunit Sivasankaran, E.Emmanuel Vincent and D.Dominique Fohr. Explaining deep learning models for speech enhancement.INTERSPEECH 2021Brno, Czech RepublicAugust 2021
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• 62 inproceedingsP.Prerak Srivastava, A.Antoine Deleforge and E.Emmanuel Vincent. Blind room parameter estimation using multiple multichannel speech recordings.WASPAA 2021- IEEE Workshop on Applications of Signal Processing to Audio and AcousticsWASPAA 2021 - IEEE Workshop on Applications of Signal Processing to Audio and AcousticsNew Paltz, NY, United StatesOctober 2021
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• 63 inproceedingsN.Nicolas Turpault, R.Romain Serizel, S.Scott Wisdom, H.Hakan Erdogan, J. R.John R Hershey, E.Eduardo Fonseca, P.Prem Seetharaman and J.Justin Salamon. Sound Event Detection and Separation: a Benchmark on Desed Synthetic Soundscapes.ICASSP 2021 - 46th International Conference on Acoustics, Speech, and Signal ProcessingToronto/Virtual, CanadaJune 2021
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• 64 inproceedings S.Scott Wisdom, H.Hakan Erdogan, D. P.Daniel P W Ellis, R.Romain Serizel, N.Nicolas Turpault, E.Eduardo Fonseca, J.Justin Salamon, P.Prem Seetharaman and J. R.John R Hershey. What’s All the FUSS About Free Universal Sound Separation Data? ICASSP 2021 - 46th International Conference on Acoustics, Speech, and Signal Processing Toronto/Virtual, Canada June 2021
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• 65 inproceedingsJ.Junichi Yamagishi, X.Xin Wang, M.Massimiliano Todisco, M.Md Sahidullah, J.Jose Patino, A.Andreas Nautsch, X.Xuechen Liu, K. A.Kong Aik Lee, T.Tomi Kinnunen, N.Nicholas Evans and H.Héctor Delgado. ASVspoof 2021: accelerating progress in spoofed and deepfake speech detection.ASVspoof 2021 Workshop - Automatic Speaker Verification and Spoofing Coutermeasures ChallengeVirtual, FranceSeptember 2021
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• 66 inproceedingsN.Nicolas Zampieri, I.Irina Illina and D.Dominique Fohr. Multiword Expression Features for Automatic Hate Speech Detection.NLDB 2021 - 26th International Conference on Natural Language & Information Systems12801Natural Language Processing and Information SystemsSaarbrücken/Virtual, GermanyJune 2021
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• 67 inproceedingsG.Georgios Zervakis, E.Emmanuel Vincent, M.Miguel Couceiro and M.Marc Schoenauer. On Refining BERT Contextualized Embeddings using Semantic Lexicons.ECML PKDD 2021 - Machine Learning with Symbolic Methods and Knowledge Graphs co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databaseshttp://ceur-ws.org/Vol-2997/paper4.pdfOnline, SpainNovember 2021
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Conferences without proceedings

• 68 inproceedingsA.Anne Bonneau. Assimilations de voisement et interférences français/allemand.RéaL2 2021 - Colloque International du Réseau d’Acquisition des Langues SecondesToulouse, FranceJuly 2021
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• 69 inproceedingsK. A.Kishore A. Kumar, S.Shefali Waldekar, G.Goutam Saha and M.Md Sahidullah. Domain-Dependent Speaker Diarization for the Third DIHARD Challenge.DIHARD 2021 - 3rd Speech Diarization Challenge WorkshopVirtual, FranceJanuary 2021
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• 70 inproceedingsN.Nicolas Zampieri, I.Irina Illina and D.Dominique Fohr. A comparative study of different features for efficient automatic hate speech detection.IPrA 2021 - 17th International Pragmatics ConferenceWinterthur, SwitzerlandJune 2021
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• 71 inproceedingsN.Nicolas Zampieri, I.Irina Illina and D.Dominique Fohr. A comparative study of different state-of-the-art NLP models for efficient automatic hate speech detection.Comments, hate speech, disinformation and public communication regulation 2021Zagreb, CroatiaSeptember 2021
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Scientific book chapters

• 72 inbookB.Benjamin Elie, C.Camille Fauth and M.Melissa Barkat-Defradas. Histoire des machines parlantes.HISTOIRE DE LA DESCRIPTION DE LA PAROLE : DE L'INTROSPECTON À L'INSTRUMENTATIONHonoré Champion2021
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Doctoral dissertations and habilitation theses

• 73 thesisT.Théo Biasutto-Lervat. Multimodal Coarticulation Modeling : Towards the animation of an intelligible talking head.Université de LorraineJanuary 2021
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• 74 thesisR.Raphaël Duroselle. Robustness of language recognition system to transmission channel.Université de Lorraine (ENIM, L-INP) / Université Paris Nanterre (ED 138 EA 369 CRIIA REDESC)October 2021
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• 75 thesisM.Manuel Pariente. Implicit and explicit phase modeling in deep learning-based source separation.Université de LorraineSeptember 2021
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• 76 thesisB. M.Brij Mohan Lal Srivastava. Speaker Anonymization: Representation, Evaluation and Formal Guarantees.Inria Lille Nord Europe - Laboratoire CRIStAL - Université de LilleDecember 2021
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• 77 thesisN.Nicolas Turpault. Analysis of scientific challenges in ambient sound recognition in real environments.Université de LorraineMay 2021
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Reports & preprints

• 78 miscD.Diego Di Carlo, P.Pinchas Tandeitnik, C.Cédric Foy, N.Nancy Bertin, A.Antoine Deleforge and S.Sharon Gannot. dEchorate: a Calibrated Room Impulse Response Dataset for Echo-aware Signal Processing.December 2021
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• 79 miscS.Sandipana Dowerah, R.Romain Serizel, D.Denis Jouvet, M.Mohammad Mohammadamini and D.Driss Matrouf. MULTICHANNEL SPEECH ENHANCEMENT FOR SPEAKER VERIFICATION IN NOISY AND REVERBERANT ENVIRONMENTS.Singapore, SingaporeDecember 2021
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• 80 miscK. A.Kishore A. Kumar, S.Shefali Waldekar, G.Goutam Saha and M.Md Sahidullah. ABSP System for The Third DIHARD Challenge.February 2021
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• 81 miscM.Mohamed Maouche, B. M.Brij Mohan Lal Srivastava, N.Nathalie Vauquier, A.Aurélien Bellet, M.Marc Tommasi and E.Emmanuel Vincent. Enhancing Speech Privacy with Slicing.October 2021
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• 82 miscI. A.Imran Ahamad Sheikh, E.Emmanuel Vincent and I.Irina Illina. Training RNN Language Models on Uncertain ASR Hypotheses in Limited Data Scenarios.August 2021
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• 83 miscI. A.Imran Ahamad Sheikh, E.Emmanuel Vincent and I.Irina Illina. Transformer versus LSTM Language Models Trained on Uncertain ASR Hypotheses in Limited Data Scenarios.October 2021
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• 84 miscB. M.Brij Mohan Lal Srivastava, M.Mohamed Maouche, M.Md Sahidullah, E.Emmanuel Vincent, A.Aurélien Bellet, M.Marc Tommasi, N.Natalia Tomashenko, X.Xin Wang and J.Junichi Yamagishi. Privacy and utility of x-vector based speaker anonymization.December 2021
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• 85 miscN.Natalia Tomashenko, X.Xin Wang, E.Emmanuel Vincent, J.Jose Patino, B. M.Brij Mohan Lal Srivastava, P.-G.Paul-Gauthier Noé, A.Andreas Nautsch, N.Nicholas Evans, J.Junichi Yamagishi, B.Benjamin O'brien, A.Anaïs Chanclu, J.-F.Jean-François Bonastre, M.Massimiliano Todisco and M.Mohamed Maouche. Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings.November 2021
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• 86 miscN.Natalia Tomashenko, X.Xin Wang, E.Emmanuel Vincent, J.Jose Patino, B. M.Brij Mohan Lal Srivastava, P.-G.Paul-Gauthier Noé, A.Andreas Nautsch, N.Nicholas Evans, J.Junichi Yamagishi, B.Benjamin O'brien, A.Anaïs Chanclu, J.-F.Jean-François Bonastre, M.Massimiliano Todisco and M.Mohamed Maouche. The VoicePrivacy 2020 Challenge: Results and findings.November 2021
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• 87 miscM. A.Mehmet Ali Tugtekin Turan, D.Dietrich Klakow, E.Emmanuel Vincent and D.Denis Jouvet. Adapting Language Models When Training on Privacy-Transformed Data.Brno, Czech RepublicApril 2021
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• 88 miscN.Nicolas Turpault, R.Romain Serizel and E.Emmanuel Vincent. Analysis of weak labels for sound event tagging.April 2021
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Scientific popularization

• 89 articleA.Akira Campbell, T.Thomas Kleinbauer, M.Marc Tommasi and E.Emmanuel Vincent. Enabling voice-based apps with European values.ERCIM News126July 2021, 38-39
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Patents

• 90 patentS.Slim Ouni, T.Théo Biasutto--Lervat and S.Sara Dahmani. Audio-driven speech animation using recurrent neutral network.WO2021023861United StatesFebruary 2021
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