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English(EN) A Tutorial on Generative Models for Music Audio

教程探讨用于音乐音频创作的生成模型

本教程论文全面概述了用于音乐音频创作的生成模型,面向熟悉神经网络训练但对音乐生成不熟悉的读者。它详细介绍了各种方法,包括神经音频编解码器、自编码器、自回归和掩码令牌模型、扩散模型以及流匹配。该论文还涵盖了采样加速、偏好优化等实际问题,并将这些技术与带有实际示例的已发表系统联系起来。 AI

影响 为进入人工智能驱动的音乐生成领域的研究人员和开发人员提供了基础资源。

排序理由 这是一篇关于音乐音频生成模型的教程论文,提交至 arXiv。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

教程探讨用于音乐音频创作的生成模型

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这是一篇关于音乐音频生成模型的教程论文,提交至 arXiv。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Mateusz Modrzejewski, Joanna Kurkowska, Dorien Herremans ·

    生成式音乐音频模型教程

    arXiv:2610.38252v1 Announce Type: cross Abstract: Music audio generation spans instrumental clips, full songs with vocals, edits of existing recordings, and systems that play alongside a musician in real time. This monograph explains the methods behind these systems for readers f…