116 citations · 441 across the 62 of their papers we have counts for
7 papers · 1 filter
Focused Concatenation for Context-Aware Neural Machine Translation
Lorenzo Lupo, Marco Dinarelli, Laurent Besacier
A straightforward approach to context-aware neural machine translation consists in feeding the standard encoder-decoder architecture with a window of consecutive sentences, formed…
SMaLL-100: Introducing Shallow Multilingual Machine Translation Model for Low-Resource Languages
Alireza Mohammadshahi, Vassilina Nikoulina, Alexandre Berard +3
In recent years, multilingual machine translation models have achieved promising performance on low-resource language pairs by sharing information between similar languages, thus e…
A Textless Metric for Speech-to-Speech Comparison
Laurent Besacier, Swen Ribeiro, Olivier Galibert +1
In this paper, we introduce a new and simple method for comparing speech utterances without relying on text transcripts. Our speech-to-speech comparison metric utilizes state-of-th…
ASR-Generated Text for Language Model Pre-training Applied to Speech Tasks
Valentin Pelloin, Franck Dary, Nicolas Herve +4
We aim at improving spoken language modeling (LM) using very large amount of automatically transcribed speech. We leverage the INA (French National Audiovisual Institute) collectio…
BERT, can HE predict contrastive focus? Predicting and controlling prominence in neural TTS using a language model
Brooke Stephenson, Laurent Besacier, Laurent Girin +1
Several recent studies have tested the use of transformer language model representations to infer prosodic features for text-to-speech synthesis (TTS). While these studies have exp…
What Do Compressed Multilingual Machine Translation Models Forget?
Alireza Mohammadshahi, Vassilina Nikoulina, Alexandre Berard +3
Recently, very large pre-trained models achieve state-of-the-art results in various natural language processing (NLP) tasks, but their size makes it more challenging to apply them…
A Study of Gender Impact in Self-supervised Models for Speech-to-Text Systems
Marcely Zanon Boito, Laurent Besacier, Natalia Tomashenko +1
Self-supervised models for speech processing emerged recently as popular foundation blocks in speech processing pipelines. These models are pre-trained on unlabeled audio data and…