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Toward Speech Separation in The Pre-Cocktail Party Problem with TasTas

Authors :
Shi, Ziqiang
Han, Jiqing
Publication Year :
2020
Publisher :
arXiv, 2020.

Abstract

In this note, we propose to use TasTas \cite{shi2020speech} for the end-to-end approach to monaural speech separation in the pre-cocktail party problem. Our experiments on the public WSJ0-5mix data corpus results in 10.41dB SDR improvement. If online voice data remixing augmentation \cite{zeghidour2020wavesplit} is adopted in training, an 11.14dB SDR improvement can be achieved. We have open-sourced our re-implementation of the DPRNN-TasNet in https://github.com/ShiZiqiang/dual-path-RNNs-DPRNNs-based-speech-separation, and our TasTas is realized based on this implementation of DPRNN-TasNet, it is believed that the results in this paper can be reproduced with ease.<br />Comment: arXiv admin note: substantial text overlap with arXiv:1902.04891

Details

Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....56c9b8e84932cfc35c1e80ec64742256
Full Text :
https://doi.org/10.48550/arxiv.2009.03692