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Section: Partnerships and Cooperations
National Initiatives
E-FRAN METAL
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Project title: Modèles Et Traces au service de l’Apprentissage des Langues
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Other partners: Interpsy, LISEC, ESPE de Lorraine, D@NTE (Univ. Versailles Saint Quentin), Sailendra SAS, ITOP Education, Rectorat.
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Participants: Theo Biasutto-Lervat, Anne Bonneau, Vincent Colotte, Dominique Fohr, Denis Jouvet, Odile Mella, Slim Ouni
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Abstract: METAL aims at improving the learning of languages (both written and oral components) through the development of new tools and the analysis of numeric traces associated with students' learning, in order to adapt to the needs and rythm of each learner.
MULTISPEECH is concerned by oral language learning aspects.
PIA2 ISITE LUE
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Abstract: The initiative aims at developing and densifying the initial perimeter of excellence, within the scope of the social and economic challenges, so as to build an original model for a leading global engineering university, with a strong emphasis on technological research and education through research. For this, we have designed LUE as an “engine” for the development of excellence, by stimulating an original dialogue between knowledge fields.
MULTISPEECH is mainly concerned with challenge number 6: “Knowledge engineering”, i.e., engineering applied to the field of knowledge and language, which represent our immaterial wealth while being a critical factor for the consistency of future choices. In 2016, this project has funded a new PhD thesis.
ANR ContNomina
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Project title: Exploitation of context for proper names recognition in diachronic audio documents
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Participants: Dominique Fohr, Irina Illina, Denis Jouvet, Odile Mella, Imran Sheikh
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Abstract: The ContNomina project was focus on the problem of proper names in automatic audio processing systems by exploiting in the most efficient way the context of the processed documents. To do this, the project has addressed the statistical modeling of contexts and of relationships between contexts and proper names; the contextualization of the recognition module (through the dynamic adjustment of the lexicon and of the language model in order to make them more accurate and certainly more relevant in terms of lexical coverage, particularly with respect to proper names); and the detection of proper names (on the one hand, in text documents for building lists of proper names, and on the other hand, in the output of the recognition system to identify spoken proper names in the audio/video data).
MULTISPEECH contributes to speech recognition and proper names handling (prediction, introduction in models, ...)
ANR DYCI2
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Project acronym: DYCI2 (http://repmus.ircam.fr/dyci2/)
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Participants: Ken Deguernel, Nathan Libermann, Emmanuel Vincent
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Abstract: The goal of this project is to design a music improvisation system which will be able to listen to the other musicians, improvise in their style, and modify its improvisation according to their feedback in real time.
MULTISPEECH is responsible for designing a system able to improvise on multiple musical dimensions (melody, harmony) across multiple time scales.
ANR JCJC KAMoulox
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Project title: Kernel additive modelling for the unmixing of large audio archives
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Abstract: The objective is to develop the theoretical and applied tools required to embed audio denoising and separation tools in web-based audio archives. The applicative scenario is to deal with large audio archives, and more precisely with the notorious “Archives du CNRS — Musée de l'homme”, gathering about 50,000 recordings dating back to the early 1900s.
ANR ArtSpeech
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Other partners: Gipsa-Lab (Grenoble), IADI (Nancy), LPP (Paris)
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Participants: Ioannis Douros, Benjamin Elie, Yves Laprie, Anastasiia Tsukanova
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Abstract: The objective is to synthesize speech from text via the numerical simulation of the human speech production processes, i.e. the articulatory, aerodynamic and acoustic aspects. Corpus based approaches have taken a hegemonic place in text to speech synthesis. They exploit very good acoustic quality speech databases while covering a high number of expressions and of phonetic contexts. This is sufficient to produce intelligible speech. However, these approaches face almost insurmountable obstacles as soon as parameters intimately related to the physical process of speech production have to be modified. On the contrary, an approach which rests on the simulation of the physical speech production process makes explicitly use of source parameters, anatomy and geometry of the vocal tract, and of a temporal supervision strategy. It thus offers direct control on the nature of the synthetic speech.
Acquisition and processing of cineMRI, new developments of acoustic simulations concercing the production of fricatives and trills, and first workds in the implementation of coarticulation in articulatory synthesis are the main activities of this year.
ANR VOCADOM
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Project acronym: VOCADOM (http://vocadom.imag.fr/)
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Project title: Robust voice command adapted to the user and to the context for AAL
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Other partners: Inria (Nancy), Univ. Lyon 2 - GREPS, THEORIS (Paris)
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Participants: Dominique Fohr, Sunit Sivasankaran, Emmanuel Vincent
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Abstract: The goal of this project is to design a robust voice control system for smart home applications. We are responsible for the speech enhancement and robust automatic speech recognition bricks.
MULTISPEECH is responsible for wake-up word detection, overlapping speech separation, and speaker recognition.
FUI VoiceHome
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Other partners: Orange, Delta Dore, Technicolor Connected Home, eSoftThings, Inria (Nancy), IRISA, LOUSTIC
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Participants: Irina Illina, Karan Nathwani, Emmanuel Vincent
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Abstract: The goal of this project was to design a robust voice control system for smart home and multimedia applications. We were responsible for the robust automatic speech recognition brick.
MULTISPEECH was responsible for robust automatic speech recognition by means of speech enhancement and uncertainty propagation.
MODALISA
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Project title: Multimodality during Language Acquisition: Interaction between Speech Signal and gestures
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Coordinator: Christelle Dodane (Praxiling, UMR 5267, Montpellier)
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Abstract: The objective of this project was to setup a multimodal platform allowing simultaneous visualization of gestural (motion capture system) and prosodic data during speech and more specifically during language acquisition.
Les contributions de MULTISPEECH concernent l’acquisition et le traitement des données multimodales grâce à la plateforme multimodale MultiMod.