20 citations · 78 across the 9 of their papers we have counts for
9 papers
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…
An Encoder-Decoder Based Audio Captioning System With Transfer and Reinforcement Learning
Xinhao Mei, Qiushi Huang, Xubo Liu +10
Automated audio captioning aims to use natural language to describe the content of audio data. This paper presents an audio captioning system with an encoder-decoder architecture,…
Peking Opera Synthesis via Duration Informed Attention Network
Yusong Wu, Shengchen Li, Chengzhu Yu +4
Peking Opera has been the most dominant form of Chinese performing art since around 200 years ago. A Peking Opera singer usually exhibits a very strong personal style via introduci…
DurIAN-SC: Duration Informed Attention Network based Singing Voice Conversion System
Liqiang Zhang, Chengzhu Yu, Heng Lu +6
Singing voice conversion is converting the timbre in the source singing to the target speaker's voice while keeping singing content the same. However, singing data for target speak…
Synthesising Expressiveness in Peking Opera via Duration Informed Attention Network
Yusong Wu, Shengchen Li, Chengzhu Yu +4
This paper presents a method that generates expressive singing voice of Peking opera. The synthesis of expressive opera singing usually requires pitch contours to be extracted as t…
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…