Bi-Sep: A Multi-Resolution Cross-Domain Monaural Speech Separation Framework
Author:
Affiliation:
1. National Taiwan Normal University,Department of Computer Science and Information Engineering,Taipei,Taiwan
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10056427/10056431/10056561.pdf?arnumber=10056561
Reference40 articles.
1. Natural Text-to-Speech Synthe-sis by Conditioning Spectrogram Predictions from Transformer Network on WaveGlow Vocoder;sanjay;ISCMI,0
2. Unsupervised sound separation using mixture invariant training;wisdom;Advances in neural information processing systems,2020
3. Speech-Transformer: A No-Recurrence Sequence-to-Sequence Model for Speech Recognition
4. Layer normalization;ba;ArXiv Preprint,2016
5. Attention Is All You Need In Speech Separation
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1. ConSep: a Noise- and Reverberation-Robust Speech Separation Framework by Magnitude Conditioning;2023 24th International Conference on Digital Signal Processing (DSP);2023-06-11
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