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ChatMusician: Understanding and Generating Music Intrinsically with LLM

Authors :
Yuan, Ruibin
Lin, Hanfeng
Wang, Yi
Tian, Zeyue
Wu, Shangda
Shen, Tianhao
Zhang, Ge
Wu, Yuhang
Liu, Cong
Zhou, Ziya
Ma, Ziyang
Xue, Liumeng
Wang, Ziyu
Liu, Qin
Zheng, Tianyu
Li, Yizhi
Ma, Yinghao
Liang, Yiming
Chi, Xiaowei
Liu, Ruibo
Wang, Zili
Li, Pengfei
Wu, Jingcheng
Lin, Chenghua
Liu, Qifeng
Jiang, Tao
Huang, Wenhao
Chen, Wenhu
Benetos, Emmanouil
Fu, Jie
Xia, Gus
Dannenberg, Roger
Xue, Wei
Kang, Shiyin
Guo, Yike
Publication Year :
2024

Abstract

While Large Language Models (LLMs) demonstrate impressive capabilities in text generation, we find that their ability has yet to be generalized to music, humanity's creative language. We introduce ChatMusician, an open-source LLM that integrates intrinsic musical abilities. It is based on continual pre-training and finetuning LLaMA2 on a text-compatible music representation, ABC notation, and the music is treated as a second language. ChatMusician can understand and generate music with a pure text tokenizer without any external multi-modal neural structures or tokenizers. Interestingly, endowing musical abilities does not harm language abilities, even achieving a slightly higher MMLU score. Our model is capable of composing well-structured, full-length music, conditioned on texts, chords, melodies, motifs, musical forms, etc, surpassing GPT-4 baseline. On our meticulously curated college-level music understanding benchmark, MusicTheoryBench, ChatMusician surpasses LLaMA2 and GPT-3.5 on zero-shot setting by a noticeable margin. Our work reveals that LLMs can be an excellent compressor for music, but there remains significant territory to be conquered. We release our 4B token music-language corpora MusicPile, the collected MusicTheoryBench, code, model and demo in GitHub.<br />Comment: GitHub: https://shanghaicannon.github.io/ChatMusician/

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2402.16153
Document Type :
Working Paper