Mathieu Balaguer — accepted AI-conference papers

2024

Exploring Pathological Speech Quality Assessment with ASR-Powered Wav2Vec2 in Data-Scarce Context

Tuan Nguyen, Corinne Fredouille, Alain Ghio, Mathieu Balaguer, Virginie Woisard

COLING 2024main

Automatic speech quality assessment has raised more attention as an alternative or support to traditional perceptual clinical evaluation. However, most research so far only gains good results on simple tasks such as binary classification, largely due to data scarcity. To deal with this challenge, cu…

Cited by 10 Source ↗PDF ↗Scholar ↗

2024

Interpretable Assessment of Speech Intelligibility Using Deep Learning: A Case Study on Speech Disorders Due to Head and Neck Cancers

Sondes Abderrazek, Corinne Fredouille, Alain Ghio, Muriel Lalain, Christine Meunier, Mathieu Balaguer +1

COLING 2024main

This paper sheds light on a relatively unexplored area which is deep learning interpretability for speech disorder assessment and characterization. Building upon a state-of-the-art methodology for the explainability and interpretability of hidden representation inside a deep-learning speech model, w…

Cited by 2 Source ↗PDF ↗Scholar ↗