61 citations · 116 across the 15 of their papers we have counts for
19 papers
LeBenchmark 2.0: a Standardized, Replicable and Enhanced Framework for Self-supervised Representations of French Speech
Titouan Parcollet, Ha Nguyen, Solene Evain +19
Self-supervised learning (SSL) is at the origin of unprecedented improvements in many different domains including computer vision and natural language processing. Speech processing…
UMLS-KGI-BERT: Data-Centric Knowledge Integration in Transformers for Biomedical Entity Recognition
Aidan Mannion, Thierry Chevalier, Didier Schwab +1
Pre-trained transformer language models (LMs) have in recent years become the dominant paradigm in applied NLP. These models have achieved state-of-the-art performance on tasks suc…
Pre-training for Speech Translation: CTC Meets Optimal Transport
Phuong-Hang Le, Hongyu Gong, Changhan Wang +3
The gap between speech and text modalities is a major challenge in speech-to-text translation (ST). Different methods have been proposed to reduce this gap, but most of them requir…
Effect Of Personalized Calibration On Gaze Estimation Using Deep-Learning
Nairit Bandyopadhyay, Sébastien Riou, Didier Schwab
With the increase in computation power and the development of new state-of-the-art deep learning algorithms, appearance-based gaze estimation is becoming more and more popular. It…
Lightweight Adapter Tuning for Multilingual Speech Translation
Hang Le, Juan Pino, Changhan Wang +3
Adapter modules were recently introduced as an efficient alternative to fine-tuning in NLP. Adapter tuning consists in freezing pretrained parameters of a model and injecting light…
Do Multilingual Neural Machine Translation Models Contain Language Pair Specific Attention Heads?
Zae Myung Kim, Laurent Besacier, Vassilina Nikoulina +1
Recent studies on the analysis of the multilingual representations focus on identifying whether there is an emergence of language-independent representations, or whether a multilin…
LeBenchmark: A Reproducible Framework for Assessing Self-Supervised Representation Learning from Speech
Solene Evain, Ha Nguyen, Hang Le +15
Self-Supervised Learning (SSL) using huge unlabeled data has been successfully explored for image and natural language processing. Recent works also investigated SSL from speech. T…
Dual-decoder Transformer for Joint Automatic Speech Recognition and Multilingual Speech Translation
Hang Le, Juan Pino, Changhan Wang +3
We introduce dual-decoder Transformer, a new model architecture that jointly performs automatic speech recognition (ASR) and multilingual speech translation (ST). Our models are ba…
Learning Term Discrimination
Jibril Frej, Phillipe Mulhem, Didier Schwab +1
Document indexing is a key component for efficient information retrieval (IR). After preprocessing steps such as stemming and stop-word removal, document indexes usually store term…
FlauBERT: Unsupervised Language Model Pre-training for French
Hang Le, Loïc Vial, Jibril Frej +7
Language models have become a key step to achieve state-of-the art results in many different Natural Language Processing (NLP) tasks. Leveraging the huge amount of unlabeled texts…
WIKIR: A Python toolkit for building a large-scale Wikipedia-based English Information Retrieval Dataset
Jibril Frej, Didier Schwab, Jean-Pierre Chevallet
Over the past years, deep learning methods allowed for new state-of-the-art results in ad-hoc information retrieval. However such methods usually require large amounts of annotated…
The LIG system for the English-Czech Text Translation Task of IWSLT 2019
Loïc Vial, Benjamin Lecouteux, Didier Schwab +2
In this paper, we present our submission for the English to Czech Text Translation Task of IWSLT 2019. Our system aims to study how pre-trained language models, used as input embed…
Sense Vocabulary Compression through the Semantic Knowledge of WordNet for Neural Word Sense Disambiguation
Loïc Vial, Benjamin Lecouteux, Didier Schwab
In this article, we tackle the issue of the limited quantity of manually sense annotated corpora for the task of word sense disambiguation, by exploiting the semantic relationships…
Improving the Coverage and the Generalization Ability of Neural Word Sense Disambiguation through Hypernymy and Hyponymy Relationships
Loïc Vial, Benjamin Lecouteux, Didier Schwab
In Word Sense Disambiguation (WSD), the predominant approach generally involves a supervised system trained on sense annotated corpora. The limited quantity of such corpora however…
Enhancing Translation Language Models with Word Embedding for Information Retrieval
Jibril Frej, Jean-Pierre Chevallet, Didier Schwab
In this paper, we explore the usage of Word Embedding semantic resources for Information Retrieval (IR) task. This embedding, produced by a shallow neural network, have been shown…
Deep Investigation of Cross-Language Plagiarism Detection Methods
Jeremy Ferrero, Laurent Besacier, Didier Schwab +1
This paper is a deep investigation of cross-language plagiarism detection methods on a new recently introduced open dataset, which contains parallel and comparable collections of d…
Comparison of Global Algorithms in Word Sense Disambiguation
Loïc Vial, Andon Tchechmedjiev, Didier Schwab
This article compares four probabilistic algorithms (global algorithms) for Word Sense Disambiguation (WSD) in terms of the number of scorer calls (local algo- rithm) and the F1 sc…
CompiLIG at SemEval-2017 Task 1: Cross-Language Plagiarism Detection Methods for Semantic Textual Similarity
Jeremy Ferrero, Frederic Agnes, Laurent Besacier +1
We present our submitted systems for Semantic Textual Similarity (STS) Track 4 at SemEval-2017. Given a pair of Spanish-English sentences, each system must estimate their semantic…
UsingWord Embedding for Cross-Language Plagiarism Detection
J. Ferrero, F. Agnes, L. Besacier +1
This paper proposes to use distributed representation of words (word embeddings) in cross-language textual similarity detection. The main contributions of this paper are the follow…