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20162024
most citedWavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing

1.9k citations · 2.8k across the 43 of their papers we have counts for

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Showing 2022Show all

8 papers · 1 filter

eess.AS2022★ 43 cited

BEATs: Audio Pre-Training with Acoustic Tokenizers

Sanyuan Chen, Yu Wu, Chengyi Wang +4

The massive growth of self-supervised learning (SSL) has been witnessed in language, vision, speech, and audio domains over the past few years. While discrete label prediction is w…

eess.AS2022

Speech separation with large-scale self-supervised learning

Zhuo Chen, Naoyuki Kanda, Jian Wu +6

Self-supervised learning (SSL) methods such as WavLM have shown promising speech separation (SS) results in small-scale simulation-based experiments. In this work, we extend the ex…

eess.AS2022

Exploring WavLM on Speech Enhancement

Hyungchan Song, Sanyuan Chen, Zhuo Chen +5

There is a surge in interest in self-supervised learning approaches for end-to-end speech encoding in recent years as they have achieved great success. Especially, WavLM showed sta…

cs.SD2022

LongFNT: Long-form Speech Recognition with Factorized Neural Transducer

Xun Gong, Yu Wu, Jinyu Li +4

Traditional automatic speech recognition~(ASR) systems usually focus on individual utterances, without considering long-form speech with useful historical information, which is mor…

cs.CL2022★ 1 cited

LAMASSU: Streaming Language-Agnostic Multilingual Speech Recognition and Translation Using Neural Transducers

Peidong Wang, Eric Sun, Jian Xue +5

Automatic speech recognition (ASR) and speech translation (ST) can both use neural transducers as the model structure. It is thus possible to use a single transducer model to perfo…

cs.CV2022★ 57 cited

Two-Stream Network for Sign Language Recognition and Translation

Yutong Chen, Ronglai Zuo, Fangyun Wei +3

Sign languages are visual languages using manual articulations and non-manual elements to convey information. For sign language recognition and translation, the majority of existin…