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20242026
most citedEnabling Auditory Large Language Models for Automatic Speech Quality Evaluation

1 citations · 3 across the 12 of their papers we have counts for

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eess.AS2025

Towards General Auditory Intelligence: Large Multimodal Models for Machine Listening and Speaking

Siyin Wang, Zengrui Jin, Changli Tang +26

In the era of large language models (LLMs) and artificial general intelligence (AGI), computer audition must evolve beyond traditional paradigms to fully leverage the capabilities…

eess.AS2025★ 1 cited

Solla: Towards a Speech-Oriented LLM That Hears Acoustic Context

Junyi Ao, Dekun Chen, Xiaohai Tian +6

Large Language Models (LLMs) have recently shown remarkable ability to process not only text but also multimodal inputs such as speech and audio. However, most existing models prim…

eess.AS2025

QualiSpeech: A Speech Quality Assessment Dataset with Natural Language Reasoning and Descriptions

Siyin Wang, Wenyi Yu, Xianzhao Chen +7

This paper explores a novel perspective to speech quality assessment by leveraging natural language descriptions, offering richer, more nuanced insights than traditional numerical…

eess.AS2024★ 1 cited

SALMONN-omni: A Codec-free LLM for Full-duplex Speech Understanding and Generation

Wenyi Yu, Siyin Wang, Xiaoyu Yang +7

Full-duplex multimodal large language models (LLMs) provide a unified framework for addressing diverse speech understanding and generation tasks, enabling more natural and seamless…

eess.AS2024★ 1 cited

Enabling Auditory Large Language Models for Automatic Speech Quality Evaluation

Siyin Wang, Wenyi Yu, Yudong Yang +10

Speech quality assessment typically requires evaluating audio from multiple aspects, such as mean opinion score (MOS) and speaker similarity (SIM) \etc., which can be challenging t…