5 citations · 5 across the 5 of their papers we have counts for
5 papers
video-SALMONN: Speech-Enhanced Audio-Visual Large Language Models
Guangzhi Sun, Wenyi Yu, Changli Tang +7
Speech understanding as an element of the more generic video understanding using audio-visual large language models (av-LLMs) is a crucial yet understudied aspect. This paper propo…
Can Large Language Models Understand Spatial Audio?
Changli Tang, Wenyi Yu, Guangzhi Sun +8
This paper explores enabling large language models (LLMs) to understand spatial information from multichannel audio, a skill currently lacking in auditory LLMs. By leveraging LLMs'…
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…
Front-End Adapter: Adapting Front-End Input of Speech based Self-Supervised Learning for Speech Recognition
Xie Chen, Ziyang Ma, Changli Tang +2
Recent years have witnessed a boom in self-supervised learning (SSL) in various areas including speech processing. Speech based SSL models present promising performance in a range…