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English(EN) Fast Diffusion-GAN Model for Generating Symbolic Music with Emotions

新的扩散GAN模型生成具有情感的符号音乐

研究人员开发了一种新颖的、集成了生成对抗网络(GAN)的扩散模型,以应对生成离散数据的符号音乐所面临的挑战。该新模型将符号音乐表示为类似图像的钢琴卷帘,并使用变分自编码器获取潜在表示,从而实现高效训练。所提出的扩散GAN模型显著减少了采样时间,仅需15次去噪步骤,而符号音乐生成通常需要数百甚至数千次,并允许控制生成音乐的情感。 AI

影响 这项研究为AI生成具有情感控制的符号音乐提供了一种更有效的方法,可能对音乐创作和AI驱动的创意工具产生影响。

排序理由 该集群包含一篇详细介绍符号音乐生成新模型的学术论文。[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 →

新的扩散GAN模型生成具有情感的符号音乐

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该集群包含一篇详细介绍符号音乐生成新模型的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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完整方法见我们的编辑标准。

报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Jincheng Zhang, Gy\"orgy Fazekas, Charalampos Saitis ·

    用于生成情感符号音乐的快速扩散-GAN模型

    arXiv:2310.14040v2 Announce Type: replace-cross Abstract: Diffusion models have shown promising results for a wide range of generative tasks with continuous data, such as image and audio synthesis. However, little progress has been made on using diffusion models to generate symbo…