7 citations · 17 across the 21 of their papers we have counts for
8 papers · 1 filter
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…
Enhancing Multimodal LLM for Detailed and Accurate Video Captioning using Multi-Round Preference Optimization
Changli Tang, Yixuan Li, Yudong Yang +5
Videos contain a wealth of information, and generating detailed and accurate descriptions in natural language is a key aspect of video understanding. In this paper, we present vide…
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…
Enhancing Audio-Language Models through Self-Supervised Post-Training with Text-Audio Pairs
Anshuman Sinha, Camille Migozzi, Aubin Rey +1
Research on multi-modal contrastive learning strategies for audio and text has rapidly gained interest. Contrastively trained Audio-Language Models (ALMs), such as CLAP, which esta…
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'…
GeminiFusion: Efficient Pixel-wise Multimodal Fusion for Vision Transformer
Ding Jia, Jianyuan Guo, Kai Han +4
Cross-modal transformers have demonstrated superiority in various vision tasks by effectively integrating different modalities. This paper first critiques prior token exchange meth…
MAV: A Multimodal, Multigenre, and Multipurpose Audio-Visual Academic Lecture Dataset
Zhe Chen, Heyang Liu, Wenyi Yu +6
Publishing open-source academic video recordings is an emergent and prevalent approach to sharing knowledge online. Such videos carry rich multimodal information including speech,…