514 citations · 918 across the 31 of their papers we have counts for
5 papers · 1 filter
Match to Win: Analysing Sequences Lengths for Efficient Self-supervised Learning in Speech and Audio
Yan Gao, Javier Fernandez-Marques, Titouan Parcollet +2
Self-supervised learning (SSL) has proven vital in speech and audio-related applications. The paradigm trains a general model on unlabeled data that can later be used to solve spec…
Federated Self-supervised Speech Representations: Are We There Yet?
Yan Gao, Javier Fernandez-Marques, Titouan Parcollet +2
The ubiquity of microphone-enabled devices has lead to large amounts of unlabelled audio data being produced at the edge. The integration of self-supervised learning (SSL) and fede…
End-to-End Speech Recognition from Federated Acoustic Models
Yan Gao, Titouan Parcollet, Salah Zaiem +4
Training Automatic Speech Recognition (ASR) models under federated learning (FL) settings has attracted a lot of attention recently. However, the FL scenarios often presented in th…
CGCNN: Complex Gabor Convolutional Neural Network on raw speech
Paul-Gauthier Noé, Titouan Parcollet, Mohamed Morchid
Convolutional Neural Networks (CNN) have been used in Automatic Speech Recognition (ASR) to learn representations directly from the raw signal instead of hand-crafted acoustic feat…
Quaternion Convolutional Neural Networks for End-to-End Automatic Speech Recognition
Titouan Parcollet, Ying Zhang, Mohamed Morchid +4
Recently, the connectionist temporal classification (CTC) model coupled with recurrent (RNN) or convolutional neural networks (CNN), made it easier to train speech recognition syst…