20 citations · 33 across the 18 of their papers we have counts for
5 papers · 1 filter
SALMONN-2: Advancing General-Purpose Hearing Abilities with Self-Supervised Representations
Xiaoyu Yang, Xuenan Xu, Wenyi Yu +10
Recent audio large language models (ALLMs) are typically built upon audio encoders trained with large amounts of supervised data. Since self-supervised learning (SSL) audio encoder…
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…
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…
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…
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…