20 citations · 78 across the 9 of their papers we have counts for
5 papers · 1 filter
MusicLDM: Enhancing Novelty in Text-to-Music Generation Using Beat-Synchronous Mixup Strategies
Ke Chen, Yusong Wu, Haohe Liu +3
Diffusion models have shown promising results in cross-modal generation tasks, including text-to-image and text-to-audio generation. However, generating music, as a special type of…
Large-scale Contrastive Language-Audio Pretraining with Feature Fusion and Keyword-to-Caption Augmentation
Yusong Wu, Ke Chen, Tianyu Zhang +4
Contrastive learning has shown remarkable success in the field of multimodal representation learning. In this paper, we propose a pipeline of contrastive language-audio pretraining…
The Chamber Ensemble Generator: Limitless High-Quality MIR Data via Generative Modeling
Yusong Wu, Josh Gardner, Ethan Manilow +3
Data is the lifeblood of modern machine learning systems, including for those in Music Information Retrieval (MIR). However, MIR has long been mired by small datasets and unreliabl…
MIDI-DDSP: Detailed Control of Musical Performance via Hierarchical Modeling
Yusong Wu, Ethan Manilow, Yi Deng +6
Musical expression requires control of both what notes are played, and how they are performed. Conventional audio synthesizers provide detailed expressive controls, but at the cost…
Learning Singing From Speech
Liqiang Zhang, Chengzhu Yu, Heng Lu +5
We propose an algorithm that is capable of synthesizing high quality target speaker's singing voice given only their normal speech samples. The proposed algorithm first integrate s…