no code implementations • LREC 2022 • Salima Mdhaffar, Valentin Pelloin, Antoine Caubrière, Gaëlle Laperriere, Sahar Ghannay, Bassam Jabaian, Nathalie Camelin, Yannick Estève
Pretrained models through self-supervised learning have been recently introduced for both acoustic and language modeling.
no code implementations • ACL (IWSLT) 2021 • Hang Le, Florentin Barbier, Ha Nguyen, Natalia Tomashenko, Salima Mdhaffar, Souhir Gabiche Gahbiche, Benjamin Lecouteux, Didier Schwab, Yannick Estève
This paper describes the ON-TRAC Consortium translation systems developed for two challenge tracks featured in the Evaluation Campaign of IWSLT 2021, low-resource speech translation and multilingual speech translation.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
no code implementations • LREC 2022 • Gaëlle Laperrière, Valentin Pelloin, Antoine Caubrière, Salima Mdhaffar, Nathalie Camelin, Sahar Ghannay, Bassam Jabaian, Yannick Estève
In this paper, we focus on the French MEDIA SLU dataset, distributed since 2005 and used as a benchmark dataset for a large number of research works.
no code implementations • 11 Sep 2023 • Titouan Parcollet, Ha Nguyen, Solene Evain, Marcely Zanon Boito, Adrien Pupier, Salima Mdhaffar, Hang Le, Sina Alisamir, Natalia Tomashenko, Marco Dinarelli, Shucong Zhang, Alexandre Allauzen, Maximin Coavoux, Yannick Esteve, Mickael Rouvier, Jerome Goulian, Benjamin Lecouteux, Francois Portet, Solange Rossato, Fabien Ringeval, Didier Schwab, Laurent Besacier
Self-supervised learning (SSL) is at the origin of unprecedented improvements in many different domains including computer vision and natural language processing.
2 code implementations • 20 Feb 2023 • Tuan Nguyen, Salima Mdhaffar, Natalia Tomashenko, Jean-François Bonastre, Yannick Estève
This paper presents a study on the use of federated learning to train an ASR model based on a wav2vec 2. 0 model pre-trained by self supervision.
no code implementations • 2 Apr 2022 • Salima Mdhaffar, Jarod Duret, Titouan Parcollet, Yannick Estève
Our approach is based on the use of an external model trained to generate a sequence of vectorial representations from text.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
no code implementations • 7 Nov 2021 • Salima Mdhaffar, Jean-François Bonastre, Marc Tommasi, Natalia Tomashenko, Yannick Estève
The widespread of powerful personal devices capable of collecting voice of their users has opened the opportunity to build speaker adapted speech recognition system (ASR) or to participate to collaborative learning of ASR.
no code implementations • 6 Nov 2021 • Natalia Tomashenko, Salima Mdhaffar, Marc Tommasi, Yannick Estève, Jean-François Bonastre
This paper investigates methods to effectively retrieve speaker information from the personalized speaker adapted neural network acoustic models (AMs) in automatic speech recognition (ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
no code implementations • 24 Jun 2021 • Sahar Ghannay, Antoine Caubrière, Salima Mdhaffar, Gaëlle Laperrière, Bassam Jabaian, Yannick Estève
More recent works on self-supervised training with unlabeled data open new perspectives in term of performance for automatic speech recognition and natural language processing.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+7
1 code implementation • 23 Apr 2021 • Solene Evain, Ha Nguyen, Hang Le, Marcely Zanon Boito, Salima Mdhaffar, Sina Alisamir, Ziyi Tong, Natalia Tomashenko, Marco Dinarelli, Titouan Parcollet, Alexandre Allauzen, Yannick Esteve, Benjamin Lecouteux, Francois Portet, Solange Rossato, Fabien Ringeval, Didier Schwab, Laurent Besacier
In this paper, we propose LeBenchmark: a reproducible framework for assessing SSL from speech.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+6
no code implementations • LREC 2020 • Salima Mdhaffar, Yannick Est{\`e}ve, Antoine Laurent, Hern, Nicolas ez, Richard Dufour, Delphine Charlet, Geraldine Damnati, Solen Quiniou, Nathalie Camelin
The use cases concern scientific fields from both speech and text processing, with language model adaptation, thematic segmentation and transcription to slide alignment.
no code implementations • JEPTALNRECITAL 2019 • Salima Mdhaffar, Yannick Est{\`e}ve, Hern, Nicolas ez, Antoine Laurent, Solen Quiniou
Les transcriptions automatiques de ces syst{\`e}mes sont de plus en plus exploitables et utilis{\'e}es dans des syst{\`e}mes complexes de traitement automatique du langage naturel, par exemple pour la traduction automatique, l{'}indexation, la recherche documentaire... Des {\'e}tudes r{\'e}centes ont propos{\'e} des m{\'e}triques permettant de comparer la qualit{\'e} des transcriptions automatiques de diff{\'e}rents syst{\`e}mes en fonction de la t{\^a}che vis{\'e}e. Dans cette {\'e}tude nous souhaitons mesurer, qualitativement, l{'}apport de l{'}adaptation automatique des mod{\`e}les de langage au domaine vis{\'e} par un cours magistral.
no code implementations • JEPTALNRECITAL 2018 • Salima Mdhaffar, Antoine Laurent, Yannick Est{\`e}ve
Cet enrichissement s{'}appuie sur des traitements automatiques du langage naturel effectu{\'e}s sur les transcriptions automatiques.