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SmoothConv and DuplexConv: Complementary Mandarin Multi-Party Conversational Speech Corpora for Speech Interaction
Chengyou Wang, Mingchen Shao, Chunjiang He +8
Recent advances in large audio language models (LALMs) have driven the development of natural and intelligent speech interaction systems. Such systems need to model complex convers…
WenetSpeech-Min: A Large-Scale Minnan Speech Corpus with Dual Transcriptions for Dialectal Speech Processing
Haoyu Zhang, Chunjiang He, Hongtao Li +17
Progress in dialectal speech technology is hindered by the scarcity of large-scale, real-world corpora. For Minnan speech, existing resources remain limited, and few provide paired…
From Script to Drama: An Agentic Framework for Controllable Multi-Speaker Dialogue TTS
Kangxiang Xia, Xinfa Zhu, HangRui Hu +8
Multi-speaker dialogue TTS requires natural speech generation, consistent speaker identity, coherent cross-turn transitions, and fine-grained control of expressive attributes such…
FA-Bench: A Benchmark for Phone- and Word-Level Timestamp Accuracy in Forced Alignment and ASR on Clean and Noisy Speech
Wei Chu, Yuanzhe Dong, Ke Tan +11
Forced alignment estimates the timestamps of each word, phone or character in speech given its transcript. Published comparisons normalize transcripts, split the data and match bou…
The Second MLC-SLM Challenge: Multilingual Conversational Speech Diarization, Recognition, and Understanding
Bingshen Mu, Mingchen Shao, Zhennan Lin +7
This paper summarizes the Interspeech2026 second Multilingual Conversational Speech Language Model (MLC-SLM) Challenge, which aims to advance the development of effective multiling…
NVV-Locator: From Transcript Tags to Acoustic Boundaries for Fine-Grained Nonverbal Vocalization Grounding
Yuang Cao, Bingshen Mu, Zhennan Lin +7
Human speech includes nonverbal vocalizations (NVVs), such as laughter, sighs, breaths, and coughs, which convey affective and interactional information. Existing approaches typica…
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…
On-Policy Self-Distillation for Multi-Dialect ASR: Mastering Dialects, Retaining Mandarin
Shuiyuan Wang, Bingshen Mu, Pengshen Zhang +6
Recent large-scale ASR models already achieve strong Mandarin recognition accuracy and have some ability to recognize Chinese dialects. However, their dialect recognition accuracy…
Listening with Time: Precise Temporal Awareness for Long-Form Audio Understanding
Mingchen Shao, Hang Su, Wenjie Tian +6
While Large Audio Language Models (LALMs) achieve strong performance on short audio, they degrade on long-form inputs. This degradation is more severe in temporal awareness tasks,…
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…
Seeing the Context: Rich Visual Context-Aware Speech Recognition via Multimodal Reasoning
Wenjie Tian, Mingchen Shao, Bingshen Mu +8
Audio-visual speech recognition (AVSR) is an extension of ASR that incorporates visual signals. Current AVSR approaches primarily focus on lip motion, largely overlooking rich cont…
EmoOmni: Bridging Emotional Understanding and Expression in Omni-Modal LLMs
Wenjie Tian, Zhixian Zhao, Jingbin Hu +4
The evolution of Omni-Modal Large Language Models~(Omni-LLMs) has revolutionized human--computer interaction, enabling unified audio-visual perception and speech response. However,…
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…
dLLM-ASR: A Faster Diffusion LLM-based Framework for Speech Recognition
Wenjie Tian, Bingshen Mu, Guobin Ma +3
Automatic speech recognition (ASR) systems based on large language models (LLMs) achieve superior performance by leveraging pretrained LLMs as decoders, but their token-by-token ge…
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…