WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing

Self-supervised learning (SSL) achieves great success in speech recognition, while limited exploration has been attempted for other speech processing tasks. As speech signal contains multi-faceted information including speaker identity, paralinguistics, spoken content, etc., learning universal repre...

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Podrobná bibliografie

Vydáno v:	IEEE journal of selected topics in signal processing Ročník 16; číslo 6; s. 1505 - 1518
Hlavní autoři:	Chen, Sanyuan, Wang, Chengyi, Chen, Zhengyang, Wu, Yu, Liu, Shujie, Chen, Zhuo, Li, Jinyu, Kanda, Naoyuki, Yoshioka, Takuya, Xiao, Xiong, Wu, Jian, Zhou, Long, Ren, Shuo, Qian, Yanmin, Qian, Yao, Zeng, Michael, Yu, Xiangzhan, Wei, Furu
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.10.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Benchmark testing Benchmarks Convolution Noise reduction Predictive models Self-supervised learning Signal processing Speech speech pre-training Speech processing Speech recognition Supervised learning Training
ISSN:	1932-4553, 1941-0484
On-line přístup:	Získat plný text
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