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20182026
most citedWavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing

1.9k citations · 2.2k across the 59 of their papers we have counts for

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5 papers · 1 filter

cs.CL2023★ 2 cited

i-Code Studio: A Configurable and Composable Framework for Integrative AI

Yuwei Fang, Mahmoud Khademi, Chenguang Zhu +8

Artificial General Intelligence (AGI) requires comprehensive understanding and generation capabilities for a variety of tasks spanning different modalities and functionalities. Int…

cs.CL2023★ 1 cited

i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data

Ziyi Yang, Mahmoud Khademi, Yichong Xu +16

The convergence of text, visual, and audio data is a key step towards human-like artificial intelligence, however the current Vision-Language-Speech landscape is dominated by encod…

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…

cs.CL2020★ 14 cited

Serialized Output Training for End-to-End Overlapped Speech Recognition

Naoyuki Kanda, Yashesh Gaur, Xiaofei Wang +2

This paper proposes serialized output training (SOT), a novel framework for multi-speaker overlapped speech recognition based on an attention-based encoder-decoder approach. Instea…

cs.CL2019★ 2 cited

DOVER: A Method for Combining Diarization Outputs

Andreas Stolcke, Takuya Yoshioka

Speech recognition and other natural language tasks have long benefited from voting-based algorithms as a method to aggregate outputs from several systems to achieve a higher accur…