1.9k citations · 3.6k across the 72 of their papers we have counts for
14 papers · 1 filter
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…
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…
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…
Simulating realistic speech overlaps improves multi-talker ASR
Muqiao Yang, Naoyuki Kanda, Xiaofei Wang +5
Multi-talker automatic speech recognition (ASR) has been studied to generate transcriptions of natural conversation including overlapping speech of multiple speakers. Due to the di…
An Adapter based Multi-label Pre-training for Speech Separation and Enhancement
Tianrui Wang, Xie Chen, Zhuo Chen +2
In recent years, self-supervised learning (SSL) has achieved tremendous success in various speech tasks due to its power to extract representations from massive unlabeled data. How…
Self-supervised learning with bi-label masked speech prediction for streaming multi-talker speech recognition
Zili Huang, Zhuo Chen, Naoyuki Kanda +6
Self-supervised learning (SSL), which utilizes the input data itself for representation learning, has achieved state-of-the-art results for various downstream speech tasks. However…
Handling Trade-Offs in Speech Separation with Sparsely-Gated Mixture of Experts
Xiaofei Wang, Zhuo Chen, Yu Shi +3
Employing a monaural speech separation (SS) model as a front-end for automatic speech recognition (ASR) involves balancing two kinds of trade-offs. First, while a larger model impr…
Real-time Speech Interruption Analysis: From Cloud to Client Deployment
Quchen Fu, Szu-Wei Fu, Yaran Fan +4
Meetings are an essential form of communication for all types of organizations, and remote collaboration systems have been much more widely used since the COVID-19 pandemic. One ma…
VarArray Meets t-SOT: Advancing the State of the Art of Streaming Distant Conversational Speech Recognition
Naoyuki Kanda, Jian Wu, Xiaofei Wang +3
This paper presents a novel streaming automatic speech recognition (ASR) framework for multi-talker overlapping speech captured by a distant microphone array with an arbitrary geom…
The Microsoft System for VoxCeleb Speaker Recognition Challenge 2022
Gang Liu, Tianyan Zhou, Yong Zhao +4
In this report, we describe our submitted system for track 2 of the VoxCeleb Speaker Recognition Challenge 2022 (VoxSRC-22). We fuse a variety of good-performing models ranging fro…
Ultra Fast Speech Separation Model with Teacher Student Learning
Sanyuan Chen, Yu Wu, Zhuo Chen +5
Transformer has been successfully applied to speech separation recently with its strong long-dependency modeling capacity using a self-attention mechanism. However, Transformer ten…
Why does Self-Supervised Learning for Speech Recognition Benefit Speaker Recognition?
Sanyuan Chen, Yu Wu, Chengyi Wang +8
Recently, self-supervised learning (SSL) has demonstrated strong performance in speaker recognition, even if the pre-training objective is designed for speech recognition. In this…
Streaming Speaker-Attributed ASR with Token-Level Speaker Embeddings
Naoyuki Kanda, Jian Wu, Yu Wu +7
This paper presents a streaming speaker-attributed automatic speech recognition (SA-ASR) model that can recognize ``who spoke what'' with low latency even when multiple people are…
Streaming Multi-Talker ASR with Token-Level Serialized Output Training
Naoyuki Kanda, Jian Wu, Yu Wu +7
This paper proposes a token-level serialized output training (t-SOT), a novel framework for streaming multi-talker automatic speech recognition (ASR). Unlike existing streaming mul…