46 citations · 115 across the 15 of their papers we have counts for
15 papers
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…
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…
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…
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…
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…
The GUA-Speech System Description for CNVSRC Challenge 2023
Shengqiang Li, Chao Lei, Baozhong Ma +2
This study describes our system for Task 1 Single-speaker Visual Speech Recognition (VSR) fixed track in the Chinese Continuous Visual Speech Recognition Challenge (CNVSRC) 2023. S…
LightGrad: Lightweight Diffusion Probabilistic Model for Text-to-Speech
Jie Chen, Xingchen Song, Zhendong Peng +3
Recent advances in neural text-to-speech (TTS) models bring thousands of TTS applications into daily life, where models are deployed in cloud to provide services for customs. Among…
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…
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…
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…
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…
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…
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…
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…
Unified Streaming and Non-streaming Two-pass End-to-end Model for Speech Recognition
Binbin Zhang, Di Wu, Zhuoyuan Yao +7
In this paper, we present a novel two-pass approach to unify streaming and non-streaming end-to-end (E2E) speech recognition in a single model. Our model adopts the hybrid CTC/atte…