1 citations · 1 across the 3 of their papers we have counts for
3 papers
Data-independent Beamforming for End-to-end Multichannel Multi-speaker ASR
Can Cui, Paul Magron, Mostafa Sadeghi +1
Automatic speech recognition (ASR) in multichannel, multi-speaker scenarios remains challenging due to ambient noise, reverberation and overlapping speakers. In this paper, we prop…
Frequency-Weighted Training Losses for Phoneme-Level DNN-based Speech Enhancement
Nasser-Eddine Monir, Paul Magron, Romain Serizel
Recent advances in deep learning have significantly improved multichannel speech enhancement algorithms, yet conventional training loss functions such as the scale-invariant signal…
Evaluating Multichannel Speech Enhancement Algorithms at the Phoneme Scale Across Genders
Nasser-Eddine Monir, Paul Magron, Romain Serizel
Multichannel speech enhancement algorithms are essential for improving the intelligibility of speech signals in noisy environments. These algorithms are usually evaluated at the ut…