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Amuse, a songwriting AI collaborator for music composers

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Amuse, a songwriting AI collaborator for music composers
Screenshot of the songwriting interface used in the user study. Credit: Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (2025). DOI: 10.1145/3706598.3713818

Wouldn’t it be great if music creators had someone to brainstorm with, help them when they’re stuck, and explore different musical directions together? Researchers at KAIST and Carnegie Mellon University (CMU) have developed AI technology similar to a fellow songwriter who helps create music.

The work is published in Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems.

The system developed by Professor Sung-Ju Lee’s research team, Amuse, is an AI-based system that converts various forms of inspiration such as text, images, and audio into harmonic structures (chord progressions) to support composition.

For example, if a user inputs a phrase, image, or sound clip such as “memories of a warm summer beach,” Amuse automatically generates and suggests chord progressions that match the inspiration.






Unlike existing generative AI, Amuse is differentiated in that it respects the user’s creative flow and naturally induces creative exploration through an interactive method that allows flexible integration and modification of AI suggestions.

The core technology of the Amuse system is a generation method that blends two approaches: a large language model creates music code based on the user’s prompt and inspiration, while another AI model, trained on real music data, filters out awkward or unnatural results using rejection sampling.

The research team conducted a user study targeting actual musicians and evaluated that Amuse has high potential as a creative companion, or a Co-Creative AI, a concept in which people and AI collaborate, rather than having a generative AI simply put together a song.

The paper, in which a Ph.D. student Yewon Kim and Professor Sung-Ju Lee of KAIST School of Electrical and Electronic Engineering and Carnegie Mellon University Professor Chris Donahue participated, demonstrated the potential of creative AI system design in both academia and industry.

Professor Sung-Ju Lee said, “Recent generative AI technology has raised concerns in that it directly imitates copyrighted content, thereby violating the copyright of the creator, or generating results one-way regardless of the creator’s intention. Accordingly, the research team was aware of this trend, paid attention to what the creator actually needs, and focused on designing an AI system centered on the creator.”

He continued, “Amuse is an attempt to explore the possibility of collaboration with AI while maintaining the initiative of the creator, and is expected to be a starting point for suggesting a more creator-friendly direction in the development of music creation tools and generative AI systems in the future.”

More information:
Yewon Kim et al, Amuse: Human-AI Collaborative Songwriting with Multimodal Inspirations, Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (2025). DOI: 10.1145/3706598.3713818

Provided by
The Korea Advanced Institute of Science and Technology (KAIST)


Citation:
Amuse, a songwriting AI collaborator for music composers (2025, May 7)
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