5 citations · 6 across the 11 of their papers we have counts for
5 papers · 1 filter
MARS-Sep: Multimodal-Aligned Reinforced Sound Separation
Zihan Zhang, Xize Cheng, Zhennan Jiang +4
Universal sound separation faces a fundamental misalignment: models optimized for low-level signal metrics often produce semantically contaminated outputs, failing to suppress perc…
T2A-Feedback: Improving Basic Capabilities of Text-to-Audio Generation via Fine-grained AI Feedback
Zehan Wang, Ke Lei, Chen Zhu +8
Text-to-audio (T2A) generation has achieved remarkable progress in generating a variety of audio outputs from language prompts. However, current state-of-the-art T2A models still s…
Unleashing the Power of Natural Audio Featuring Multiple Sound Sources
Xize Cheng, Slytherin Wang, Zehan Wang +3
Universal sound separation aims to extract clean audio tracks corresponding to distinct events from mixed audio, which is critical for artificial auditory perception. However, curr…
Prompt-Singer: Controllable Singing-Voice-Synthesis with Natural Language Prompt
Yongqi Wang, Ruofan Hu, Rongjie Huang +6
Recent singing-voice-synthesis (SVS) methods have achieved remarkable audio quality and naturalness, yet they lack the capability to control the style attributes of the synthesized…
TransFace: Unit-Based Audio-Visual Speech Synthesizer for Talking Head Translation
Xize Cheng, Rongjie Huang, Linjun Li +7
Direct speech-to-speech translation achieves high-quality results through the introduction of discrete units obtained from self-supervised learning. This approach circumvents delay…