activity
20212025
most citedWenetSpeech: A 10000+ Hours Multi-domain Mandarin Corpus for Speech Recognition

32 citations · 92 across the 16 of their papers we have counts for

collaborators

16 papers

cs.SD2025

Adapting Whisper for Streaming Speech Recognition via Two-Pass Decoding

Haoran Zhou, Xingchen Song, Brendan Fahy +9

OpenAI Whisper is a family of robust Automatic Speech Recognition (ASR) models trained on 680,000 hours of audio. However, its encoder-decoder architecture, trained with a sequence…

eess.AS2024

TouchASP: Elastic Automatic Speech Perception that Everyone Can Touch

Xingchen Song, Chengdong Liang, Binbin Zhang +9

Large Automatic Speech Recognition (ASR) models demand a vast number of parameters, copious amounts of data, and significant computational resources during the training process. Ho…

cs.SD2024

TouchTTS: An Embarrassingly Simple TTS Framework that Everyone Can Touch

Xingchen Song, Mengtao Xing, Changwei Ma +9

It is well known that LLM-based systems are data-hungry. Recent LLM-based TTS works typically employ complex data processing pipelines to obtain high-quality training data. These s…

eess.AS2024

HydraFormer: One Encoder For All Subsampling Rates

Yaoxun Xu, Xingchen Song, Zhiyong Wu +3

In automatic speech recognition, subsampling is essential for tackling diverse scenarios. However, the inadequacy of a single subsampling rate to address various real-world situati…

cs.CL2024

U2++ MoE: Scaling 4.7x parameters with minimal impact on RTF

Xingchen Song, Di Wu, Binbin Zhang +5

Scale has opened new frontiers in natural language processing, but at a high cost. In response, by learning to only activate a subset of parameters in training and inference, Mixtu…

cs.SD2023★ 16 cited

ZeroPrompt: Streaming Acoustic Encoders are Zero-Shot Masked LMs

Xingchen Song, Di Wu, Binbin Zhang +4

In this paper, we present ZeroPrompt (Figure 1-(a)) and the corresponding Prompt-and-Refine strategy (Figure 3), two simple but effective \textbf{training-free} methods to decrease…

cs.IT2023

Power Adaptation for Suborbital Downlink with Stochastic Satellites Interference

Yihao He, Juntao Ma, Zhendong Peng +1

This paper investigates downlink power adaptation for the suborbital node in suborbital-ground communication systems, which are subject to extremely high reliability and ultra-low…

cs.SD2022

Fast-U2++: Fast and Accurate End-to-End Speech Recognition in Joint CTC/Attention Frames

Chengdong Liang, Xiao-Lei Zhang, BinBin Zhang +5

Recently, the unified streaming and non-streaming two-pass (U2/U2++) end-to-end model for speech recognition has shown great performance in terms of streaming capability, accuracy…

cs.SD2022★ 1 cited

TrimTail: Low-Latency Streaming ASR with Simple but Effective Spectrogram-Level Length Penalty

Xingchen Song, Di Wu, Zhiyong Wu +6

In this paper, we present TrimTail, a simple but effective emission regularization method to improve the latency of streaming ASR models. The core idea of TrimTail is to apply leng…

cs.SD2022

FusionFormer: Fusing Operations in Transformer for Efficient Streaming Speech Recognition

Xingchen Song, Di Wu, Binbin Zhang +8

The recently proposed Conformer architecture which combines convolution with attention to capture both local and global dependencies has become the \textit{de facto} backbone model…

eess.SP2022

Error Propagation and Overhead Reduced Channel Estimation for RIS-Aided Multi-User mmWave Systems

Zhendong Peng, Cunhua Pan, Gui Zhou +1

In this paper, we propose a novel two-stage based uplink channel estimation strategy with reduced pilot overhead and error propagation for a reconfigurable intelligent surface (RIS…

eess.SP2022★ 3 cited

Channel Estimation for RIS-Aided Multi-User mmWave Systems with Uniform Planar Arrays

Zhendong Peng, Gui Zhou, Cunhua Pan +4

In this paper, we adopt a three-stage based uplink channel estimation protocol with reduced pilot overhead for an reconfigurable intelligent surface (RIS)-aided multi-user (MU) mil…

cs.SD2022★ 2 cited

WeNet 2.0: More Productive End-to-End Speech Recognition Toolkit

Binbin Zhang, Di Wu, Zhendong Peng +7

Recently, we made available WeNet, a production-oriented end-to-end speech recognition toolkit, which introduces a unified two-pass (U2) framework and a built-in runtime to address…

cs.SD2021★ 32 cited

WenetSpeech: A 10000+ Hours Multi-domain Mandarin Corpus for Speech Recognition

Binbin Zhang, Hang Lv, Pengcheng Guo +9

In this paper, we present WenetSpeech, a multi-domain Mandarin corpus consisting of 10000+ hours high-quality labeled speech, 2400+ hours weakly labeled speech, and about 10000 hou…

cs.SD2021★ 22 cited

U2++: Unified Two-pass Bidirectional End-to-end Model for Speech Recognition

Di Wu, Binbin Zhang, Chao Yang +4

The unified streaming and non-streaming two-pass (U2) end-to-end model for speech recognition has shown great performance in terms of streaming capability, accuracy, real-time fact…

cs.SD2021★ 16 cited

WeNet: Production oriented Streaming and Non-streaming End-to-End Speech Recognition Toolkit

Zhuoyuan Yao, Di Wu, Xiong Wang +7

In this paper, we propose an open source, production first, and production ready speech recognition toolkit called WeNet in which a new two-pass approach is implemented to unify st…