5 papers
QA-MoE: Towards a Continuous Reliability Spectrum with Quality-Aware Mixture of Experts for Robust Multimodal Sentiment Analysis
Yitong Zhu, Yuxuan Jiang, Guanxuan Jiang +4
Multimodal Sentiment Analysis (MSA) aims to infer human sentiment from textual, acoustic, and visual signals. In real-world scenarios, however, multimodal inputs are often compromi…
Omni2Sound: Towards Unified Video-Text-to-Audio Generation
Yusheng Dai, Zehua Chen, Yuxuan Jiang +4
Training a unified model integrating video-to-audio (V2A), text-to-audio (T2A), and joint video-text-to-audio (VT2A) generation offers significant application flexibility, yet face…
ControlAudio: Tackling Text-Guided, Timing-Indicated and Intelligible Audio Generation via Progressive Diffusion Modeling
Yuxuan Jiang, Zehua Chen, Zeqian Ju +3
Text-to-audio (TTA) generation with fine-grained control signals, e.g., precise timing control or intelligible speech content, has been explored in recent works. However, constrain…
AudioMoG: Guiding Audio Generation with Mixture-of-Guidance
Junyou Wang, Zehua Chen, Binjie Yuan +4
The design of diffusion-based audio generation systems has been investigated from diverse perspectives, such as data space, network architecture, and conditioning techniques, while…
FreeAudio: Training-Free Timing Planning for Controllable Long-Form Text-to-Audio Generation
Yuxuan Jiang, Zehua Chen, Zeqian Ju +3
Text-to-audio (T2A) generation has achieved promising results with the recent advances in generative models. However, because of the limited quality and quantity of temporally-alig…