most citedQualitative Evaluation of Language Model Rescoring in Automatic Speech Recognition

6 citations · 8 across the 7 of their papers we have counts for

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7 papers

cs.CL2026

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…

cs.CL20261 cited

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…

cs.CL2026

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…

cs.CL20261 cited

HATS: An Open data set Integrating Human Perception Applied to the Evaluation of Automatic Speech Recognition Metrics

Thibault Bañeras Roux, Jane Wottawa, Mickael Rouvier +2

Conventionally, Automatic Speech Recognition (ASR) systems are evaluated on their ability to correctly recognize each word contained in a speech signal. In this context, the word e…

cs.CL20266 cited

Qualitative Evaluation of Language Model Rescoring in Automatic Speech Recognition

Thibault Bañeras-Roux, Mickaël Rouvier, Jane Wottawa +1

Evaluating automatic speech recognition (ASR) systems is a classical but difficult and still open problem, which often boils down to focusing only on the word error rate (WER). How…

cs.CL2026

Closing the Speech-Text Gap with Limited Audio for Effective Domain Adaptation in LLM-Based ASR

Thibault Bañeras-Roux, Sergio Burdisso, Esaú Villatoro-Tello +9

Conventional end-to-end automatic speech recognition (ASR) systems rely on paired speech-text data for domain adaptation. Recent LLM-based ASR architectures connect a speech encode…