Loop Copilot: Conducting AI Ensembles for Music Generation and Iterative Editing

Creating music is iterative, requiring varied methods at each stage. However, existing AI music systems fall short in orchestrating multiple subsystems for diverse needs. To address this gap, we introduce Loop Copilot, a novel system that enables users to generate and iteratively refine music throug...

Full description

Saved in:
Bibliographic Details
Published in:arXiv.org 2024-08
Main Authors: Zhang, Yixiao, Maezawa, Akira, Xia, Gus, Yamamoto, Kazuhiko, Dixon, Simon
Format: Article
Language:English
Subjects:
Iterative methods
Large language models
Music
Subsystems
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Creating music is iterative, requiring varied methods at each stage. However, existing AI music systems fall short in orchestrating multiple subsystems for diverse needs. To address this gap, we introduce Loop Copilot, a novel system that enables users to generate and iteratively refine music through an interactive, multi-round dialogue interface. The system uses a large language model to interpret user intentions and select appropriate AI models for task execution. Each backend model is specialized for a specific task, and their outputs are aggregated to meet the user's requirements. To ensure musical coherence, essential attributes are maintained in a centralized table. We evaluate the effectiveness of the proposed system through semi-structured interviews and questionnaires, highlighting its utility not only in facilitating music creation but also its potential for broader applications.
ISSN:2331-8422