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20192022
most citedWavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing

1.9k citations · 4k across the 25 of their papers we have counts for

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Showing 2021Show all

8 papers · 1 filter

eess.AS2021

Continuous Speech Separation with Recurrent Selective Attention Network

Yixuan Zhang, Zhuo Chen, Jian Wu +4

While permutation invariant training (PIT) based continuous speech separation (CSS) significantly improves the conversation transcription accuracy, it often suffers from speech lea…

cs.CL2021★ 10 cited

UniSpeech-SAT: Universal Speech Representation Learning with Speaker Aware Pre-Training

Sanyuan Chen, Yu Wu, Chengyi Wang +8

Self-supervised learning (SSL) is a long-standing goal for speech processing, since it utilizes large-scale unlabeled data and avoids extensive human labeling. Recent years witness…

cs.CL2021★ 1.9k cited

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

Sanyuan Chen, Chengyi Wang, Zhengyang Chen +15

Self-supervised learning (SSL) achieves great success in speech recognition, while limited exploration has been attempted for other speech processing tasks. As speech signal contai…

eess.AS2021

Investigation of Practical Aspects of Single Channel Speech Separation for ASR

Jian Wu, Zhuo Chen, Sanyuan Chen +5

Speech separation has been successfully applied as a frontend processing module of conversation transcription systems thanks to its ability to handle overlapped speech and its flex…

eess.AS2021★ 1 cited

A Comparative Study of Modular and Joint Approaches for Speaker-Attributed ASR on Monaural Long-Form Audio

Naoyuki Kanda, Xiong Xiao, Jian Wu +6

Speaker-attributed automatic speech recognition (SA-ASR) is a task to recognize "who spoke what" from multi-talker recordings. An SA-ASR system usually consists of multiple modules…

eess.AS2021

Sequence-level Confidence Classifier for ASR Utterance Accuracy and Application to Acoustic Models

Amber Afshan, Kshitiz Kumar, Jian Wu

Scores from traditional confidence classifiers (CCs) in automatic speech recognition (ASR) systems lack universal interpretation and vary with updates to the underlying confidence…

cs.SD2021★ 8 cited

AISHELL-4: An Open Source Dataset for Speech Enhancement, Separation, Recognition and Speaker Diarization in Conference Scenario

Yihui Fu, Luyao Cheng, Shubo Lv +10

In this paper, we present AISHELL-4, a sizable real-recorded Mandarin speech dataset collected by 8-channel circular microphone array for speech processing in conference scenario.…

eess.AS2021★ 12 cited

Speaker attribution with voice profiles by graph-based semi-supervised learning

Jixuan Wang, Xiong Xiao, Jian Wu +3

Speaker attribution is required in many real-world applications, such as meeting transcription, where speaker identity is assigned to each utterance according to speaker voice prof…