title: Loop Copilot: Conducting AI Ensembles for Music Generation and Iterative
    Editing
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.
paper_authors._id: 6531df22a1162a3f8799de8f
paper_authors.name: Yixiao Zhang
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-10-20T08:09:23.365Z
paper_authors._id: 6376a5aad49217e154f580aa
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/1668720030380-noauth.jpeg
paper_authors.fullname: Yixiao ZHang
paper_authors.type: user
paper_authors.user: ldzhangyx
paper_authors._id: 6531df22a1162a3f8799de90
paper_authors.name: Akira Maezawa
paper_authors._id: 6531df22a1162a3f8799de91
paper_authors.name: Gus Xia
paper_authors._id: 6531df22a1162a3f8799de92
paper_authors.name: Kazuhiko Yamamoto
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-10-20T08:09:41.324Z
paper_authors._id: 630470b59aef62c4013b7b78
paper_authors.avatarUrl: /avatars/7c326ed8c71e8ab1baff99892755c888.svg
paper_authors.fullname: Kazuhiko Yamamoto
paper_authors.type: user
paper_authors.user: yamotulp
paper_authors._id: 6531df22a1162a3f8799de93
paper_authors.name: Simon Dixon
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-10-20T08:09:48.113Z
paper_authors._id: 643ac28aff50448bcfc24b19
paper_authors.avatarUrl: /avatars/18d201b94829bae9985dbb4ec618e1ff.svg
paper_authors.fullname: Simon Dixon
paper_authors.type: user
paper_authors.user: Dexdixon
paper_title: Loop Copilot: Conducting AI Ensembles for Music Generation and Iterative
    Editing
paper_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.
paper_ai_keywords: large language model interactive, multi-round dialogue interface backend model centralized table