1 code implementation • 16 Nov 2023 • Ilaria Manco, Benno Weck, Seungheon Doh, Minz Won, Yixiao Zhang, Dmitry Bogdanov, Yusong Wu, Ke Chen, Philip Tovstogan, Emmanouil Benetos, Elio Quinton, György Fazekas, Juhan Nam
We introduce the Song Describer dataset (SDD), a new crowdsourced corpus of high-quality audio-caption pairs, designed for the evaluation of music-and-language models.
1 code implementation • 3 Aug 2023 • Ke Chen, Yusong Wu, Haohe Liu, Marianna Nezhurina, Taylor Berg-Kirkpatrick, Shlomo Dubnov
Diffusion models have shown promising results in cross-modal generation tasks, including text-to-image and text-to-audio generation.
1 code implementation • 28 Sep 2022 • Yusong Wu, Josh Gardner, Ethan Manilow, Ian Simon, Curtis Hawthorne, Jesse Engel
We call this system the Chamber Ensemble Generator (CEG), and use it to generate a large dataset of chorales from four different chamber ensembles (CocoChorales).
1 code implementation • ICLR 2022 • Yusong Wu, Ethan Manilow, Yi Deng, Rigel Swavely, Kyle Kastner, Tim Cooijmans, Aaron Courville, Cheng-Zhi Anna Huang, Jesse Engel
Musical expression requires control of both what notes are played, and how they are performed.
1 code implementation • 5 Aug 2021 • Xinhao Mei, Qiushi Huang, Xubo Liu, Gengyun Chen, Jingqian Wu, Yusong Wu, Jinzheng Zhao, Shengchen Li, Tom Ko, H Lilian Tang, Xi Shao, Mark D. Plumbley, Wenwu Wang
Automated audio captioning aims to use natural language to describe the content of audio data.
no code implementations • 7 Aug 2020 • Yusong Wu, Shengchen Li, Chengzhu Yu, Heng Lu, Chao Weng, Liqiang Zhang, Dong Yu
In this work, we propose to deal with this issue and synthesize expressive Peking Opera singing from the music score based on the Duration Informed Attention Network (DurIAN) framework.
no code implementations • 27 Dec 2019 • Yusong Wu, Shengchen Li, Chengzhu Yu, Heng Lu, Chao Weng, Liqiang Zhang, Dong Yu
This paper presents a method that generates expressive singing voice of Peking opera.
no code implementations • 20 Dec 2019 • Liqiang Zhang, Chengzhu Yu, Heng Lu, Chao Weng, Yusong Wu, Xiang Xie, Zijin Li, Dong Yu
The proposed algorithm first integrate speech and singing synthesis into a unified framework, and learns universal speaker embeddings that are shareable between speech and singing synthesis tasks.