Deep neural networks for oral and written language processing (RAPACE)Date: 10/2017 – 09/2020Funding: RFI AltanStic 2020Call: Défis scientifiques 2016Partners: LINA (France)URL: https://lium.univ-lemans.fr/en/rapace/LIUM Participant(s): Antoine CaubrièreAntoine LaurentYannick EstèveThe RAPACE project focuses on the implementation of a deep neural architecture, associating specialized hidden layers, to develop a fully neural system of speech processing. The aim is to […]
Learning and applications of distributed multilingual representationsStarting: 01/10/2015PhD Student: Alexis ConneauAdvisor(s): Paul Deléglise (LIUM, LST)Co-advisor(s): Loïc Barrault (LIUM, LST), Holger Schwenk (Facebook)Funding: CIFRE (Facebook)Learning and applications of distributed multilingual representations
JOKe and Empathy of a Robot/ECA: Towards social and affective relations with a robot (JOKER)Date: 01/2014 – 07/2017Funding: EU H2020Call: CHIST-ERA 2012Partners: LIMSI (coordinateur) (France), UCD (Irlande), UMONS (Belgique), KOC University (Turquie)URL: https://lium.univ-lemans.fr/en/joker/LIUM Participant(s): Yannick EstèveNathalie CamelinSimon PetitrenaudSylvain MeignierDaniel LuzzatiThis project will build and develop JOKER, a generic intelligent user interface providing a multimodal dialogue […]
Automatic structuring of audio documentsStarting: 01/10/2012PhD Student: Abdessalam BouchekifAdvisor(s): Yannick EstèveCo-advisor(s): Nathalie CamelinFunding: Contrat Orange LabsThe topic structuring is an area that has attracted much attention in the Natural Language Processing community. Indeed, topic structuring is considered as the starting point of several applications such as information retrieval, summarization and topic modeling. In this thesis, […]
AdVanced ERror Analysis for speech recognition (VERA)Date: 01/2013 – 01/2016Funding: ANRCall: BlancPartners: LNE (France), LPP (France), LIMSI (France)URL: https://lium.univ-lemans.fr/en/vera/LIUM Participant(s): Nathalie CamelinDaniel LuzzatiPaul DelégliseSylvain MeignierYannick EstèveThe VERA project aims at developing tools for diagnostic, localization, and measurements of automatic transcription errors. This project is based on a consortium of first-rate academic actors in this field. […]
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