Seed-Music: A Unified Framework for High Quality and Controlled Music
  Generation
Authors: name: Ye Bai, name: Haonan Chen, name: Jitong Chen, name: Zhuo Chen, name: Yi Deng, name: Xiaohong Dong, name: Lamtharn Hantrakul, name: Weituo Hao, name: Qingqing Huang, name: Zhongyi Huang, name: Dongya Jia, name: Feihu La, name: Duc Le, name: Bochen Li, name: Chumin Li, name: Hui Li, name: Xingxing Li, name: Shouda Liu, name: Wei-Tsung Lu, name: Yiqing Lu, name: Andrew Shaw, name: Janne Spijkervet, name: Yakun Sun, name: Bo Wang, name: Ju-Chiang Wang, name: Yuping Wang, name: Yuxuan Wang, name: Ling Xu, name: Yifeng Yang, name: Chao Yao, name: Shuo Zhang, name: Yang Zhang, name: Yilin Zhang, name: Hang Zhao, name: Ziyi Zhao, name: Dejian Zhong, name: Shicen Zhou, name: Pei Zou

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 .