用四个协作智能体自动生成符合音乐逻辑的高音和声。
An Agent-Based Framework for Automated Higher-Voice Harmony Generation
- 分四步：解析乐谱、理解和弦、生成旋律、合成音频。
- 能生成与主旋律节奏、旋律都匹配的高质量和声。
- 适合音乐创作人或AI作曲研究者使用。
自动生成音乐上连贯且悦耳的和声仍是算法作曲领域的重大挑战。本文提出一种基于智能体的高级和声生成框架，采用多智能体协同架构。系统包含四个专用智能体：音乐输入智能体负责解析并标准化输入乐谱；和弦知识智能体（基于Chord-Former Transformer模型）解析复杂和弦符号并输出构成音符；和声生成智能体利用Harmony-GPT与Rhythm-Net（RNN）生成旋律与节奏协调的和声线；音频制作智能体则通过基于GAN的符号到音频合成器将符号化输出转换为高保真音频。该模块化设计模拟了人类音乐家的协作过程，实现稳健的数据处理、深层理论理解、创造性编排与真实音频合成，最终可为给定旋律生成复杂且语境恰当的高音和声。
原文摘要 · Abstract (English)
The generation of musically coherent and aesthetically pleasing harmony remains a significant challenge in the field of algorithmic composition. This paper introduces an innovative Agentic AI-enabled Higher Harmony Music Generator, a multi-agent system designed to create harmony in a collaborative and modular fashion. Our framework comprises four specialized agents: a Music-Ingestion Agent for parsing and standardizing input musical scores; a Chord-Knowledge Agent, powered by a Chord-Former (Transformer model), to interpret and provide the constituent notes of complex chord symbols; a Harmony-Generation Agent, which utilizes a Harmony-GPT and a Rhythm-Net (RNN) to compose a melodically and rhythmically complementary harmony line; and an Audio-Production Agent that employs a GAN-based Symbolic-to-Audio Synthesizer to render the final symbolic output into high-fidelity audio. By delegating specific tasks to specialized agents, our system effectively mimics the collaborative process of human musicians. This modular, agent-based approach allows for robust data processing, deep theoretical understanding, creative composition, and realistic audio synthesis, culminating in a system capable of generating sophisticated and contextually appropriate higher-voice harmonies for given melodies.
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