activity
20222025
most citedOn the Use of Semantically-Aligned Speech Representations for Spoken Language Understanding

2 citations · 2 across the 3 of their papers we have counts for

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5 papers · 1 filter

cs.CL2025

In-domain SSL pre-training and streaming ASR

Jarod Duret, Salima Mdhaffar, Gaëlle Laperrière +6

In this study, we investigate the benefits of domain-specific self-supervised pre-training for both offline and streaming ASR in Air Traffic Control (ATC) environments. We train BE…

cs.CL2024

A dual task learning approach to fine-tune a multilingual semantic speech encoder for Spoken Language Understanding

Gaëlle Laperrière, Sahar Ghannay, Bassam Jabaian +1

Self-Supervised Learning is vastly used to efficiently represent speech for Spoken Language Understanding, gradually replacing conventional approaches. Meanwhile, textual SSL model…

cs.CL2024

New Semantic Task for the French Spoken Language Understanding MEDIA Benchmark

Nadège Alavoine, Gaëlle Laperriere, Christophe Servan +2

Intent classification and slot-filling are essential tasks of Spoken Language Understanding (SLU). In most SLUsystems, those tasks are realized by independent modules. For about fi…

cs.CL2023

Semantic enrichment towards efficient speech representations

Gaëlle Laperrière, Ha Nguyen, Sahar Ghannay +2

Over the past few years, self-supervised learned speech representations have emerged as fruitful replacements for conventional surface representations when solving Spoken Language…

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…