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Seed-Music: A Unified Framework for High Quality and Controlled Music Generation

13 September 2024
Ye Bai
Haonan Chen
Jitong Chen
Zhuo Chen
Yi Deng
Xiaohong Dong
Lamtharn Hantrakul
Weituo Hao
Qingqing Huang
Zhongyi Huang
Dongya Jia
Feihu La
Duc Le
Bochen Li
Chumin Li
Hui Li
X. Li
Shouda Liu
Wei-Tsung Lu
Y. Lu
Andrew Shaw
Janne Spijkervet
Yakun Sun
Bo Wang
Ju-Chiang Wang
Yuping Wang
Yuxuan Wang
Ling Xu
Yifeng Yang
Chao Yao
Shuo Zhang
Yang Zhang
Yilin Zhang
Hang Zhao
Ziyi Zhao
Dejian Zhong
Shicen Zhou
Pei Zou
    DiffM
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Abstract

We introduce Seed-Music, a suite of music generation systems capable of producing high-quality music with fine-grained style control. Our unified framework leverages both auto-regressive language modeling and diffusion approaches to support two key music creation workflows: controlled music generation and post-production editing. For controlled music generation, our system enables vocal music generation with performance controls from multi-modal inputs, including style descriptions, audio references, musical scores, and voice prompts. For post-production editing, it offers interactive tools for editing lyrics and vocal melodies directly in the generated audio. We encourage readers to listen to demo audio examples at https://team.doubao.com/seed-music "https://team.doubao.com/seed-music".

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