20 citations · 47 across the 14 of their papers we have counts for
14 papers
Summary of the ChinaVoices Challenge 2026: Data, Tasks, Baseline, and Methods
Yujie Liao, Bingshen Mu, Shuiyuan Wang +5
This paper summarizes the ChinaVoices Challenge 2026, which aims to establish unified task definitions and evaluation conditions for Chinese dialect speech processing and to advanc…
DiaScriber: A Speech LLM for Joint Diarization and Transcription in Multi-Speaker Scenarios
Bingshen Mu, Xian Shi, Xiong Wang +6
Multi-speaker automatic speech recognition (MSASR) aims to jointly predict content transcriptions, speaker identities, and timestamps, thereby addressing the key question of "who s…
Semantic-Aware Interruption Detection in Spoken Dialogue Systems: Benchmark, Metric, and Model
Kangxiang Xia, Bingshen Mu, Xian Shi +2
Achieving natural full-duplex interaction in spoken dialogue systems (SDS) remains a challenge due to the difficulty of accurately detecting user interruptions. Current solutions a…
LLM-ForcedAligner: A Non-Autoregressive and Accurate LLM-Based Forced Aligner for Multilingual and Long-Form Speech
Bingshen Mu, Xian Shi, Xiong Wang +3
Forced alignment (FA) predicts start and end timestamps for words or characters in speech, but existing methods are language-specific and prone to cumulative temporal shifts. The m…
SeACo-Paraformer: A Non-Autoregressive ASR System with Flexible and Effective Hotword Customization Ability
Xian Shi, Yexin Yang, Zerui Li +3
Hotword customization is one of the concerned issues remained in ASR field - it is of value to enable users of ASR systems to customize names of entities, persons and other phrases…
Accurate and Reliable Confidence Estimation Based on Non-Autoregressive End-to-End Speech Recognition System
Xian Shi, Haoneng Luo, Zhifu Gao +2
Estimating confidence scores for recognition results is a classic task in ASR field and of vital importance for kinds of downstream tasks and training strategies. Previous end-to-e…
BAT: Boundary aware transducer for memory-efficient and low-latency ASR
Keyu An, Xian Shi, Shiliang Zhang
Recently, recurrent neural network transducer (RNN-T) gains increasing popularity due to its natural streaming capability as well as superior performance. Nevertheless, RNN-T train…
FunASR: A Fundamental End-to-End Speech Recognition Toolkit
Zhifu Gao, Zerui Li, Jiaming Wang +8
This paper introduces FunASR, an open-source speech recognition toolkit designed to bridge the gap between academic research and industrial applications. FunASR offers models train…
Achieving Timestamp Prediction While Recognizing with Non-Autoregressive End-to-End ASR Model
Xian Shi, Yanni Chen, Shiliang Zhang +1
Conventional ASR systems use frame-level phoneme posterior to conduct force-alignment~(FA) and provide timestamps, while end-to-end ASR systems especially AED based ones are short…
Linguistic-Acoustic Similarity Based Accent Shift for Accent Recognition
Qijie Shao, Jinghao Yan, Jian Kang +4
General accent recognition (AR) models tend to directly extract low-level information from spectrums, which always significantly overfit on speakers or channels. Considering accent…
Darts-Conformer: Towards Efficient Gradient-Based Neural Architecture Search For End-to-End ASR
Xian Shi, Pan Zhou, Wei Chen +1
Neural architecture search (NAS) has been successfully applied to tasks like image classification and language modeling for finding efficient high-performance network architectures…
The Accented English Speech Recognition Challenge 2020: Open Datasets, Tracks, Baselines, Results and Methods
Xian Shi, Fan Yu, Yizhou Lu +5
The variety of accents has posed a big challenge to speech recognition. The Accented English Speech Recognition Challenge (AESRC2020) is designed for providing a common testbed and…
Cascade RNN-Transducer: Syllable Based Streaming On-device Mandarin Speech Recognition with a Syllable-to-Character Converter
Xiong Wang, Zhuoyuan Yao, Xian Shi +1
End-to-end models are favored in automatic speech recognition (ASR) because of its simplified system structure and superior performance. Among these models, recurrent neural networ…
The ASRU 2019 Mandarin-English Code-Switching Speech Recognition Challenge: Open Datasets, Tracks, Methods and Results
Xian Shi, Qiangze Feng, Lei Xie
Code-switching (CS) is a common phenomenon and recognizing CS speech is challenging. But CS speech data is scarce and there' s no common testbed in relevant research. This paper de…