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
Published: 2024-09-13 22:06:18

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 .