activity
20242026
most citedOSUM: Advancing Open Speech Understanding Models with Limited Resources in Academia

1 citations · 1 across the 11 of their papers we have counts for

collaborators

16 papers

eess.AS2026

RefTAG: Reflection-aware Temporal Audio Grounding in Large Audio Language Models

Yuhang Dai, Xin Shu, Zhennan Lin +5

Temporal audio grounding requires locating every occurrence of a queried target, making both occurrence counts and interval boundaries essential. We propose RefTAG, a post-training…

eess.AS2026

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…

eess.AS2026

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…

cs.SD2026

Bridging the Modality Gap in Long-Form Clinical Audio: A Comparative Study of Lightweight and Heavyweight End-to-End SOAP Generation

Ziyu Zhang, Mingchen Shao, Wenjie Tian +3

Automating clinical documentation from long-form doctor-patient conversations remains challenging for modern audio-language models. While cascaded ASR systems perform well, end-to-…

eess.AS2026

GigaSpeechBench: A Real-World Multilingual Speech-to-Text Benchmark

Yujie Tu, Yifan Yang, Tianrui Wang +35

While modern ASR systems achieve low error rates on high-resource benchmarks, such performance often overestimates real-world robustness. Existing evaluations address challenges in…

eess.AS2026

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,…

cs.SD2026

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…

cs.AI2026

LLM-MINE: Large Language Model based Alzheimer's Disease and Related Dementias Phenotypes Mining from Clinical Notes

Mingchen Shao, Yuzhang Xie, Carl Yang +1

Accurate extraction of Alzheimer's Disease and Related Dementias (ADRD) phenotypes from electronic health records (EHR) is critical for early-stage detection and disease staging. H…

cs.SD2026

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…

cs.SD2025

Towards Building Speech Large Language Models for Multitask Understanding in Low-Resource Languages

Mingchen Shao, Bingshen Mu, Chengyou Wang +4

Speech large language models (SLLMs) built on speech encoders, adapters, and LLMs demonstrate remarkable multitask understanding performance in high-resource languages such as Engl…

eess.AS2025

Summary on The Multilingual Conversational Speech Language Model Challenge: Datasets, Tasks, Baselines, and Methods

Bingshen Mu, Pengcheng Guo, Zhaokai Sun +8

This paper summarizes the Interspeech2025 Multilingual Conversational Speech Language Model (MLC-SLM) challenge, which aims to advance the exploration of building effective multili…

cs.SD2025

OSUM-EChat: Enhancing End-to-End Empathetic Spoken Chatbot via Understanding-Driven Spoken Dialogue

Xuelong Geng, Qijie Shao, Hongfei Xue +20

Empathy is crucial in enabling natural interactions within spoken dialogue systems, allowing machines to recognize and respond appropriately to paralinguistic cues such as age, gen…

cs.SD2025

Weakly Supervised Data Refinement and Flexible Sequence Compression for Efficient Thai LLM-based ASR

Mingchen Shao, Xinfa Zhu, Chengyou Wang +6

Despite remarkable achievements, automatic speech recognition (ASR) in low-resource scenarios still faces two challenges: high-quality data scarcity and high computational demands.…

cs.SD2025★ 1 cited

OSUM: Advancing Open Speech Understanding Models with Limited Resources in Academia

Xuelong Geng, Kun Wei, Qijie Shao +18

Large Language Models (LLMs) have made significant progress in various downstream tasks, inspiring the development of Speech Understanding Language Models (SULMs) to enable compreh…

eess.AS2024

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…

cs.SD2024

Unveiling the Potential of LLM-Based ASR on Chinese Open-Source Datasets

Xuelong Geng, Tianyi Xu, Kun Wei +9

Large Language Models (LLMs) have demonstrated unparalleled effectiveness in various NLP tasks, and integrating LLMs with automatic speech recognition (ASR) is becoming a mainstrea…