SunoCaps:一个基于文本提示的AI生成音乐的新型数据集,带有情感注释
M Civit1,2,3, V Drai-Zerbib2, D Lizcano4
1Department of Communication and Education, Universidad Loyola Andalucía. Av. de las Universidades s/n. 41704 Sevilla, Spain.
Data in brief
|August 20, 2024
概括
SunoCaps数据集介绍了人工智能生成的歌曲,使用专家音乐描述作为提示. 这一新数据集有助于开发更好的音乐生成和情绪分析工具.
科学领域:
- 音乐信息检索 音乐信息检索
- 人工智能的人工智能
- 计算音乐学 计算音乐学
背景情况:
- 音乐信息检索 (MIR) 领域需要各种数据集来推进音乐技术.
- 现有的数据集往往缺乏足够多样性或人工智能生成的内容,用于特定的研究途径.
- 自动音乐生成 (AMG) 为创建新型数据集提供了机会.
研究的目的:
- 介绍SunoCaps数据集,这是一个由人工智能生成的音乐的新集合.
- 为了利用 MusicCaps 数据集中的专家描述来生成新的音乐作品.
- 为改善音乐生成模型和情绪分析提供资源.
主要方法:
- 使用最先进的Suno发电机来创作基于音频的音乐.
- 为64个选定的MusicCaps作品 (共256个条目) 每个生成四个变化.
- 包括专家对即时对齐和被生成的音乐所唤起的离散情绪的注释.
主要成果:
- 成功创建了SunoCaps数据集,其中包含256个人工智能生成的音乐作品.
- 对每个作品进行注释提示生成对齐和离散情绪.
- 建立了评估AI音乐生成质量和情感影响的基础.
结论:
- SunoCaps数据集为MIR社区提供了宝贵的资源.
- 它促进了自动音乐生成验证和优化方面的进步.
- 该数据集支持对多层人工智能架构和音乐情感估计的研究.
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