activity
20172022
most citedOn the use of Self-supervised Pre-trained Acoustic and Linguistic Features for Continuous Speech Emotion Recognition

55 citations · 80 across the 11 of their papers we have counts for

collaborators

19 papers

cs.CL20222 cited

On the Use of Semantically-Aligned Speech Representations for Spoken Language Understanding

Gaëlle Laperrière, Valentin Pelloin, Mickaël Rouvier +2

In this paper we examine the use of semantically-aligned speech representations for end-to-end spoken language understanding (SLU). We employ the recently-introduced SAMU-XLSR mode…

cs.CL2022

ON-TRAC Consortium Systems for the IWSLT 2022 Dialect and Low-resource Speech Translation Tasks

Marcely Zanon Boito, John Ortega, Hugo Riguidel +8

This paper describes the ON-TRAC Consortium translation systems developed for two challenge tracks featured in the Evaluation Campaign of IWSLT 2022: low-resource and dialect speec…

cs.CL2022

End-to-end model for named entity recognition from speech without paired training data

Salima Mdhaffar, Jarod Duret, Titouan Parcollet +1

Recent works showed that end-to-end neural approaches tend to become very popular for spoken language understanding (SLU). Through the term end-to-end, one considers the use of a s…

cs.CL2021

Retrieving Speaker Information from Personalized Acoustic Models for Speech Recognition

Salima Mdhaffar, Jean-François Bonastre, Marc Tommasi +2

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 par…

cs.CL2021

Impact of Encoding and Segmentation Strategies on End-to-End Simultaneous Speech Translation

Ha Nguyen, Yannick Estève, Laurent Besacier

Boosted by the simultaneous translation shared task at IWSLT 2020, promising end-to-end online speech translation approaches were recently proposed. They consist in incrementally e…

cs.CL20211 cited

An Empirical Study of End-to-end Simultaneous Speech Translation Decoding Strategies

Ha Nguyen, Yannick Estève, Laurent Besacier

This paper proposes a decoding strategy for end-to-end simultaneous speech translation. We leverage end-to-end models trained in offline mode and conduct an empirical study for two…