深度学习赋能音乐创作：算法创新与智能协同的未来图景

旻 史(东莞理工学院，中国)

摘要

本文探讨了AI（Artificial Intelligence 人工智能）在音乐创作领域的核心方向：音乐生成算法的演进和人机协同创作。首先，综述了音乐生成算法从早期规则系统到现代深度学习（如RNN, VAE）的演变历程，并分析了代表性应用案例（如Magenta, DeepBach）。其次，重点剖析了AI作为灵感源与实时创作伙伴的角色，探讨了智能协同创作（如AIVA, Magenta Jam）的实现机制、技术挑战（实时性、理解力）及突破。最后，展望了未来发展趋势，包括更富创造性的算法、多模态生成、深度人机协同及可解释性平衡。本研究旨在厘清AI音乐创作的技术脉络，为相关研究和实践提供参考。

关键词

人工智能；音乐创作；生成算法；深度学习；实时协同

参考

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DOI: http://dx.doi.org/10.12345/cai.v4i6.28430