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20232025
most citedFine-grained Audio-Visual Joint Representations for Multimodal Large Language Models

5 citations · 7 across the 11 of their papers we have counts for

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6 papers · 1 filter

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

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.AS20241 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

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…

eess.AS20235 cited

Fine-grained Audio-Visual Joint Representations for Multimodal Large Language Models

Guangzhi Sun, Wenyi Yu, Changli Tang +6

Audio-visual large language models (LLM) have drawn significant attention, yet the fine-grained combination of both input streams is rather under-explored, which is challenging but…

eess.AS2023

Connecting Speech Encoder and Large Language Model for ASR

Wenyi Yu, Changli Tang, Guangzhi Sun +6

The impressive capability and versatility of large language models (LLMs) have aroused increasing attention in automatic speech recognition (ASR), with several pioneering studies a…