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cs.LG2025
Evaluating and Improving the Robustness of Speech Command Recognition Models to Noise and Distribution Shifts
Anaïs Baranger, Lucas Maison
Although prior work in computer vision has shown strong correlations between in-distribution (ID) and out-of-distribution (OOD) accuracies, such relationships remain underexplored…
cs.LG2023
Compression of Recurrent Neural Networks using Matrix Factorization
Lucas Maison, Hélion du Mas des Bourboux, Thomas Courtat
Compressing neural networks is a key step when deploying models for real-time or embedded applications. Factorizing the model's matrices using low-rank approximations is a promisin…
cs.LG2023
Improving Accented Speech Recognition with Multi-Domain Training
Lucas Maison, Yannick Estève
Thanks to the rise of self-supervised learning, automatic speech recognition (ASR) systems now achieve near-human performance on a wide variety of datasets. However, they still lac…