183 citations · 234 across the 2 of their papers we have counts for
2 papers
eess.AS2020★ 183 cited
LibriMix: An Open-Source Dataset for Generalizable Speech Separation
Joris Cosentino, Manuel Pariente, Samuele Cornell +2
In recent years, wsj0-2mix has become the reference dataset for single-channel speech separation. Most deep learning-based speech separation models today are benchmarked on it. How…
eess.AS2020★ 51 cited
Asteroid: the PyTorch-based audio source separation toolkit for researchers
Manuel Pariente, Samuele Cornell, Joris Cosentino +11
This paper describes Asteroid, the PyTorch-based audio source separation toolkit for researchers. Inspired by the most successful neural source separation systems, it provides all…