82 citations · 147 across the 18 of their papers we have counts for
19 papers
The SLT 2026 SmartGlasses Challenge: Benchmarking Egocentric Multi-Talker Speech Recognition and Understanding with Audio-Language Models
Dehui Gao, Zhixian Zhao, Zhennan Lin +14
Recent advances in large language models (LLMs) and multimodal LLMs (MLLMs) have created new opportunities for wearable speech interfaces, with smart glasses providing an egocentri…
NüshuVoice: Reviving the Voice of Endangered Nüshu with Pitch-Aware Text-to-Speech
Hongkun Yang, Xinhui Yi, Xiyan Zhao +13
Nüshu is an endangered phonetic script historically used by women in Jiangyong County, southern Hunan, China. While existing computational studies of Nüshu mainly focus on textual…
Full-Duplex Interaction in Spoken Dialogue Systems: A Comprehensive Study from the ICASSP 2026 HumDial Challenge
Chengyou Wang, Hongfei Xue, Guojian Li +6
Full-duplex interaction, where speakers and listeners converse simultaneously, is a key element of human communication often missing from traditional spoken dialogue systems. These…
The ICASSP 2026 HumDial Challenge: Benchmarking Human-like Spoken Dialogue Systems in the LLM Era
Zhixian Zhao, Shuiyuan Wang, Guojian Li +12
Driven by the rapid advancement of Large Language Models (LLMs), particularly Audio-LLMs and Omni-models, spoken dialogue systems have evolved significantly, progressively narrowin…
WenetSpeech-Wu: Datasets, Benchmarks, and Models for a Unified Chinese Wu Dialect Speech Processing Ecosystem
Chengyou Wang, Mingchen Shao, Jingbin Hu +11
Speech processing for low-resource dialects remains a fundamental challenge in developing inclusive and robust speech technologies. Despite its linguistic significance and large sp…
WenetSpeech-Chuan: A Large-Scale Sichuanese Corpus with Rich Annotation for Dialectal Speech Processing
Yuhang Dai, Ziyu Zhang, Shuai Wang +13
The scarcity of large-scale, open-source data for dialects severely hinders progress in speech technology, a challenge particularly acute for the widely spoken Sichuanese dialects…
WenetSpeech-Yue: A Large-scale Cantonese Speech Corpus with Multi-dimensional Annotation
Longhao Li, Zhao Guo, Hongjie Chen +15
The development of speech understanding and generation has been significantly accelerated by the availability of large-scale, high-quality speech datasets. Among these, ASR and TTS…
AISHELL-5: The First Open-Source In-Car Multi-Channel Multi-Speaker Speech Dataset for Automatic Speech Diarization and Recognition
Yuhang Dai, He Wang, Xingchen Li +8
This paper delineates AISHELL-5, the first open-source in-car multi-channel multi-speaker Mandarin automatic speech recognition (ASR) dataset. AISHLL-5 includes two parts: (1) over…
Findings of the 2024 Mandarin Stuttering Event Detection and Automatic Speech Recognition Challenge
Hongfei Xue, Rong Gong, Mingchen Shao +10
The StutteringSpeech Challenge focuses on advancing speech technologies for people who stutter, specifically targeting Stuttering Event Detection (SED) and Automatic Speech Recogni…
AS-70: A Mandarin stuttered speech dataset for automatic speech recognition and stuttering event detection
Rong Gong, Hongfei Xue, Lezhi Wang +11
The rapid advancements in speech technologies over the past two decades have led to human-level performance in tasks like automatic speech recognition (ASR) for fluent speech. Howe…
ICMC-ASR: The ICASSP 2024 In-Car Multi-Channel Automatic Speech Recognition Challenge
He Wang, Pengcheng Guo, Yue Li +13
To promote speech processing and recognition research in driving scenarios, we build on the success of the Intelligent Cockpit Speech Recognition Challenge (ICSRC) held at ISCSLP 2…
The ISCSLP 2022 Intelligent Cockpit Speech Recognition Challenge (ICSRC): Dataset, Tracks, Baseline and Results
Ao Zhang, Fan Yu, Kaixun Huang +7
This paper summarizes the outcomes from the ISCSLP 2022 Intelligent Cockpit Speech Recognition Challenge (ICSRC). We first address the necessity of the challenge and then introduce…
Summary On The ICASSP 2022 Multi-Channel Multi-Party Meeting Transcription Grand Challenge
Fan Yu, Shiliang Zhang, Pengcheng Guo +13
The ICASSP 2022 Multi-channel Multi-party Meeting Transcription Grand Challenge (M2MeT) focuses on one of the most valuable and the most challenging scenarios of speech technologie…
M2MeT: The ICASSP 2022 Multi-Channel Multi-Party Meeting Transcription Challenge
Fan Yu, Shiliang Zhang, Yihui Fu +9
Recent development of speech processing, such as speech recognition, speaker diarization, etc., has inspired numerous applications of speech technologies. The meeting scenario is o…
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…
The Multi-speaker Multi-style Voice Cloning Challenge 2021
Qicong Xie, Xiaohai Tian, Guanghou Liu +9
The Multi-speaker Multi-style Voice Cloning Challenge (M2VoC) aims to provide a common sizable dataset as well as a fair testbed for the benchmarking of the popular voice cloning t…
INTERSPEECH 2021 ConferencingSpeech Challenge: Towards Far-field Multi-Channel Speech Enhancement for Video Conferencing
Wei Rao, Yihui Fu, Yanxin Hu +11
The ConferencingSpeech 2021 challenge is proposed to stimulate research on far-field multi-channel speech enhancement for video conferencing. The challenge consists of two separate…
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.…
AISHELL-3: A Multi-speaker Mandarin TTS Corpus and the Baselines
Yao Shi, Hui Bu, Xin Xu +2
In this paper, we present AISHELL-3, a large-scale and high-fidelity multi-speaker Mandarin speech corpus which could be used to train multi-speaker Text-to-Speech (TTS) systems. T…