Skim: Skipping Memory Lstm for Low-Latency Real-Time Continuous Speech Separation-Reference-Cited by-同舟云学术

Skim: Skipping Memory Lstm for Low-Latency Real-Time Continuous Speech Separation

Published:2022-05-23 Issue: Volume: Page:
ISSN:
Container-title:ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Li Chenda¹,Yang Lei²,Wang Weiqin²,Qian Yanmin¹

Affiliation:

1. Shanghai Jiao Tong University,MoE Key Lab of Artificial Intelligence, AI Institute X-LANCE Lab,Department of Computer Science and Engineering,Shanghai,China

2. Samsung Research China - Beijing (SRC-B)

Funder

National Key Research and Development Program of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9745891/9746004/09746372.pdf?arnumber=9746372

Reference33 articles.

1. FurcaNeXt: End-to-end monaural speech separation with dynamic gated dilated temporal convolutional networks;zhang;Multi-Media Modelling,2020

2. Divide and Conquer: A Deep CASA Approach to Talker-Independent Monaural Speaker Separation

3. Speaker-Independent Speech Separation With Deep Attractor Network

4. Single-Channel Multi-Speaker Separation Using Deep Clustering

5. Dual-Path RNN: Efficient Long Sequence Modeling for Time-Domain Single-Channel Speech Separation

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