1 citations · 2 across the 9 of their papers we have counts for
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Inference-time Scaling for Diffusion-based Audio Super-resolution
Yizhu Jin, Zhen Ye, Zeyue Tian +4
Diffusion models have demonstrated remarkable success in generative tasks, including audio super-resolution (SR). In many applications like movie post-production and album masterin…
DualDub: Video-to-Soundtrack Generation via Joint Speech and Background Audio Synthesis
Wenjie Tian, Xinfa Zhu, Haohe Liu +6
While recent video-to-audio (V2A) models can generate realistic background audio from visual input, they largely overlook speech, an essential part of many video soundtracks. This…
YuE: Scaling Open Foundation Models for Long-Form Music Generation
Ruibin Yuan, Hanfeng Lin, Shuyue Guo +55
We tackle the task of long-form music generation--particularly the challenging \textbf{lyrics-to-song} problem--by introducing YuE, a family of open foundation models based on the…
Llasa: Scaling Train-Time and Inference-Time Compute for Llama-based Speech Synthesis
Zhen Ye, Xinfa Zhu, Chi-Min Chan +17
Recent advances in text-based large language models (LLMs), particularly in the GPT series and the o1 model, have demonstrated the effectiveness of scaling both training-time and i…