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

1 citations · 3 across the 9 of their papers we have counts for

collaborators

11 papers

eess.AS2026

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…

eess.AS2026

HumDial-EIBench: A Human-Recorded Multi-Turn Emotional Intelligence Benchmark for Audio Language Models

Shuiyuan Wang, Zhixian Zhao, Hongfei Xue +5

Evaluating the emotional intelligence (EI) of audio language models (ALMs) is critical. However, existing benchmarks mostly rely on synthesized speech, are limited to single-turn i…

cs.SD2026

OSUM-Pangu: An Open-Source Multidimension Speech Understanding Foundation Model Built upon OpenPangu on Ascend NPUs

Yujie Liao, Xuelong Geng, Hongfei Xue +2

Recent advancements in Speech Large Language Models have significantly enhanced multi-dimensional speech understanding. However, the majority of high-performance frameworks are pre…

cs.SD20261 cited

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…

cs.SD2025

Serial-Parallel Dual-Path Architecture for Speaking Style Recognition

Guojian Li, Qijie Shao, Zhixian Zhao +3

Speaking Style Recognition (SSR) identifies a speaker's speaking style characteristics from speech. Existing style recognition approaches primarily rely on linguistic information,…

cs.CL2025

Easy Turn: Integrating Acoustic and Linguistic Modalities for Robust Turn-Taking in Full-Duplex Spoken Dialogue Systems

Guojian Li, Chengyou Wang, Hongfei Xue +8

Full-duplex interaction is crucial for natural human-machine communication, yet remains challenging as it requires robust turn-taking detection to decide when the system should spe…