为AI生成音乐设计可溯源的智能代理系统，解决版权与收益分配难题。
From Generation to Attribution: Music AI Agent Architectures for the Post-Streaming Era
- 将音乐拆分为可追踪的块（Blocks），嵌入创作流程中
- 每使用一次即触发溯源事件，实现实时版权结算
- 适合关注公平版权分配的音乐创作者与平台开发者
生成式AI正在重塑音乐创作，但其快速发展暴露了归属权、权利管理和经济模式的结构性缺口。与以往从现场演出到录音、下载、流媒体的演变不同，AI彻底改变了音乐的全生命周期，模糊了创作、分发与变现的界限。然而现有流媒体系统因版税流动不透明且集中，难以应对AI生产带来的规模与复杂性。我们提出一种基于内容的Music AI Agent架构，通过块级检索与智能体编排，将归属信息直接嵌入创作流程。系统以会话式迭代交互为基础，将音乐组织为存储于BlockDB的细粒度组件（Blocks）；每次使用均触发归属层事件，实现透明溯源与实时结算。该框架将AI从生成工具重构为公平AI媒体平台的基础设施，通过细粒度归属、公平补偿与参与式互动，指向一个后流媒体时代：音乐不再是静态目录，而是一个协作且可适应的生态系统。
原文摘要 · Abstract (English)
Generative AI is reshaping music creation, but its rapid growth exposes structural gaps in attribution, rights management, and economic models. Unlike past media shifts, from live performance to recordings, downloads, and streaming, AI transforms the entire lifecycle of music, collapsing boundaries between creation, distribution, and monetization. However, existing streaming systems, with opaque and concentrated royalty flows, are ill-equipped to handle the scale and complexity of AI-driven production. We propose a content-based Music AI Agent architecture that embeds attribution directly into the creative workflow through block-level retrieval and agentic orchestration. Designed for iterative, session-based interaction, the system organizes music into granular components (Blocks) stored in BlockDB; each use triggers an Attribution Layer event for transparent provenance and real-time settlement. This framework reframes AI from a generative tool into infrastructure for a Fair AI Media Platform. By enabling fine-grained attribution, equitable compensation, and participatory engagement, it points toward a post-streaming paradigm where music functions not as a static catalog but as a collaborative and adaptive ecosystem.
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