CoLyricist: Enhancing Lyric Writing with AI through Workflow-Aligned Support

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Authors: Masahiro Yoshida, B. Q. Li, Songyan Zhao, Qinyi Zhou, Shiwei Hu, Xiang 'Anthony Chen, Nanyun Peng
Cited by: 1
References: 50

Abstract

We propose CoLyricist, an AI-assisted lyric writing tool designed to support the typical workflows of experienced lyricists and enhance their creative efficiency. While lyricists have unique processes, many follow common stages. Tools that fail to accommodate these stages challenge integration into creative practices. Existing research and tools lack sufficient understanding of these songwriting stages and their associated challenges, resulting in ineffective designs. Through a formative study involving semi-structured interviews with 10 experienced lyricists, we identified four key stages: Theme Setting, Ideation, Drafting Lyrics, and Melody Fitting. CoLyricist addresses these needs by incorporating tailored AI-driven support for each stage, optimizing the lyric writing process to be more seamless and efficient. To examine whether this workflow-aligned design also benefits those without prior experience, we conducted a user study with 16 participants, including both experienced and novice lyricists. Results showed that CoLyricist enhances the songwriting experience across skill levels. Novice users especially appreciated the Melody-Fitting feature, while experienced users valued the Ideation support.

Fields of Study & Subjects

Music Technology and Sound Studies Artificial Intelligence in Games Digital Humanities and Scholarship

Publication details

Journal / source
Proceedings of the 31st International Conference on Intelligent User Interfaces
Publisher
ACM
Pages
1387–1410
Publication date
3 March 2026
Language
EN