1.9k citations · 4k across the 25 of their papers we have counts for
25 papers
Multilingual Transformer Language Model for Speech Recognition in Low-resource Languages
Li Miao, Jian Wu, Piyush Behre +2
It is challenging to train and deploy Transformer LMs for hybrid speech recognition 2nd pass re-ranking in low-resource languages due to (1) data scarcity in low-resource languages…
Deploying self-supervised learning in the wild for hybrid automatic speech recognition
Mostafa Karimi, Changliang Liu, Kenichi Kumatani +3
Self-supervised learning (SSL) methods have proven to be very successful in automatic speech recognition (ASR). These great improvements have been reported mostly based on highly c…
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…
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…
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…
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…
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…
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…
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…
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.…
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…
Multi-Channel Automatic Speech Recognition Using Deep Complex Unet
Yuxiang Kong, Jian Wu, Quandong Wang +4
The front-end module in multi-channel automatic speech recognition (ASR) systems mainly use microphone array techniques to produce enhanced signals in noisy conditions with reverbe…
DESNet: A Multi-channel Network for Simultaneous Speech Dereverberation, Enhancement and Separation
Yihui Fu, Jian Wu, Yanxin Hu +2
In this paper, we propose a multi-channel network for simultaneous speech dereverberation, enhancement and separation (DESNet). To enable gradient propagation and joint optimizatio…
Microsoft Speaker Diarization System for the VoxCeleb Speaker Recognition Challenge 2020
Xiong Xiao, Naoyuki Kanda, Zhuo Chen +10
This paper describes the Microsoft speaker diarization system for monaural multi-talker recordings in the wild, evaluated at the diarization track of the VoxCeleb Speaker Recogniti…
DCCRN: Deep Complex Convolution Recurrent Network for Phase-Aware Speech Enhancement
Yanxin Hu, Yun Liu, Shubo Lv +6
Speech enhancement has benefited from the success of deep learning in terms of intelligibility and perceptual quality. Conventional time-frequency (TF) domain methods focus on pred…
An End-to-end Architecture of Online Multi-channel Speech Separation
Jian Wu, Zhuo Chen, Jinyu Li +5
Multi-speaker speech recognition has been one of the keychallenges in conversation transcription as it breaks the singleactive speaker assumption employed by most state-of-the-arts…
Channel-wise Subband Input for Better Voice and Accompaniment Separation on High Resolution Music
Haohe Liu, Lei Xie, Jian Wu +1
This paper presents a new input format, channel-wise subband input (CWS), for convolutional neural networks (CNN) based music source separation (MSS) models in the frequency domain…
ResNeXt and Res2Net Structures for Speaker Verification
Tianyan Zhou, Yong Zhao, Jian Wu
The ResNet-based architecture has been widely adopted to extract speaker embeddings for text-independent speaker verification systems. By introducing the residual connections to th…
Speaker diarization with session-level speaker embedding refinement using graph neural networks
Jixuan Wang, Xiong Xiao, Jian Wu +3
Deep speaker embedding models have been commonly used as a building block for speaker diarization systems; however, the speaker embedding model is usually trained according to a gl…
Audio-visual Recognition of Overlapped speech for the LRS2 dataset
Jianwei Yu, Shi-Xiong Zhang, Jian Wu +7
Automatic recognition of overlapped speech remains a highly challenging task to date. Motivated by the bimodal nature of human speech perception, this paper investigates the use of…
Continuous speech separation: dataset and analysis
Zhuo Chen, Takuya Yoshioka, Liang Lu +6
This paper describes a dataset and protocols for evaluating continuous speech separation algorithms. Most prior studies on speech separation use pre-segmented signals of artificial…
End-to-End Multi-Channel Speech Separation
Rongzhi Gu, Jian Wu, Shi-Xiong Zhang +6
The end-to-end approach for single-channel speech separation has been studied recently and shown promising results. This paper extended the previous approach and proposed a new end…
A comprehensive study of speech separation: spectrogram vs waveform separation
Fahimeh Bahmaninezhad, Jian Wu, Rongzhi Gu +4
Speech separation has been studied widely for single-channel close-talk microphone recordings over the past few years; developed solutions are mostly in frequency-domain. Recently,…
Improved Speaker-Dependent Separation for CHiME-5 Challenge
Jian Wu, Yong Xu, Shi-Xiong Zhang +4
This paper summarizes several follow-up contributions for improving our submitted NWPU speaker-dependent system for CHiME-5 challenge, which aims to solve the problem of multi-chan…