2 citations · 3 across the 12 of their papers we have counts for
13 papers · 1 filter
Generative vs. Encoder Large Language Models for ASR Evaluation: A Comparative Study
Thibault Bañeras-Roux, Shashi Kumar, Driss Khalil +6
Automatic Speech Recognition (ASR) is typically evaluated using Word Error Rate (WER), which poorly reflects semantic similarity. While embedding-based metrics correlate better wit…
Streaming Neural Speech Codecs through Time-Invariant Representations
Kélian Estève, Salima Mhdaffar, Mickael Rouvier +2
Neural speech codecs are increasingly used as intermediate representations in codec-based speech generation systems. TiCodec introduces a factorized representation that separates t…
Evaluation of Automatic Speech Recognition Using Generative Large Language Models
Thibault Bañeras-Roux, Shashi Kumar, Driss Khalil +6
Automatic Speech Recognition (ASR) is traditionally evaluated using Word Error Rate (WER), a metric that is insensitive to meaning. Embedding-based semantic metrics are better corr…
A Comprehensive Analysis of Tokenization and Self-Supervised Learning in End-to-End Automatic Speech Recognition applied on French Language
Thibault Bañeras-Roux, Mickael Rouvier, Jane Wottawa +1
The performance of end-to-end automatic speech recognition (ASR) systems enables their increasing integration into numerous applications. While there are various benefits to such s…
A Paradigm for Interpreting Metrics and Identifying Critical Errors in Automatic Speech Recognition
Thibault Bañeras-Roux, Mickael Rouvier, Jane Wottawa +1
The most commonly used metrics for evaluating automatic speech transcriptions, namely Word Error Rate (WER) and Character Error Rate (CER), have been heavily criticized for their p…
MedInjection-FR: Exploring the Role of Native, Synthetic, and Translated Data in Biomedical Instruction Tuning
Ikram Belmadani, Oumaima El Khettari, Pacôme Constant dit Beaufils +2
Instruction tuning has become essential for adapting large language models (LLMs) to follow domain-specific prompts. Yet, in specialized fields such as medicine, the scarcity of hi…
An Empirical Analysis of Discrete Unit Representations in Speech Language Modeling Pre-training
Yanis Labrak, Richard Dufour, Mickaël Rouvier
This paper investigates discrete unit representations in Speech Language Models (SLMs), focusing on optimizing speech modeling during continual pre-training. In this paper, we syst…
Improving Social Determinants of Health Documentation in French EHRs Using Large Language Models
Adrien Bazoge, Pacôme Constant dit Beaufils, Mohammed Hmitouch +6
Social determinants of health (SDoH) significantly influence health outcomes, shaping disease progression, treatment adherence, and health disparities. However, their documentation…
A Benchmark of French ASR Systems Based on Error Severity
Antoine Tholly, Jane Wottawa, Mickael Rouvier +1
Automatic Speech Recognition (ASR) transcription errors are commonly assessed using metrics that compare them with a reference transcription, such as Word Error Rate (WER), which m…
Zero-Shot End-To-End Spoken Question Answering In Medical Domain
Yanis Labrak, Adel Moumen, Richard Dufour +1
In the rapidly evolving landscape of spoken question-answering (SQA), the integration of large language models (LLMs) has emerged as a transformative development. Conventional appr…
DrBenchmark: A Large Language Understanding Evaluation Benchmark for French Biomedical Domain
Yanis Labrak, Adrien Bazoge, Oumaima El Khettari +8
The biomedical domain has sparked a significant interest in the field of Natural Language Processing (NLP), which has seen substantial advancements with pre-trained language models…
How Important Is Tokenization in French Medical Masked Language Models?
Yanis Labrak, Adrien Bazoge, Beatrice Daille +2
Subword tokenization has become the prevailing standard in the field of natural language processing (NLP) over recent years, primarily due to the widespread utilization of pre-trai…
BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains
Yanis Labrak, Adrien Bazoge, Emmanuel Morin +3
Large Language Models (LLMs) have demonstrated remarkable versatility in recent years, offering potential applications across specialized domains such as healthcare and medicine. D…