分析用户如何用文字生成AI音乐，揭示创作趋势与语言偏好。
Data-Driven Analysis of Text-Conditioned AI-Generated Music: A Case Study with Suno and Udio
- 用文本嵌入与聚类分析用户生成的歌词、标签和提示词。
- 发现歌词主题集中于情感表达与虚构叙事，语言以英文为主。
- 展示交互式可视化结果，适合研究AI音乐文化与用户行为的人参考。
Suno和Udio等在线AI音乐平台允许用户通过文字提示生成音乐，目前已吸引数十万用户使用，部分作品甚至进入广告和多国音乐榜单。本文基于2024年5月至10月期间的大量用户生成音乐数据，结合先进的文本嵌入模型、降维与聚类方法，分析了提示词、标签和歌词内容，并自动标注与可视化处理结果。研究揭示了歌词中的显著主题、语言偏好以及用户常用的提示策略，还发现了利用元标签引导模型的特殊尝试。为推动对AI生成音乐这一新兴文化现象的音乐学研究，作者公开了代码与数据资源。
原文摘要 · Abstract (English)
Online AI platforms for creating music from text prompts (AI music), such as Suno and Udio, are now being used by hundreds of thousands of users. Some AI music is appearing in advertising, and even charting, in multiple countries. How are these platforms being used? What subjects are inspiring their users? This article answers these questions for Suno and Udio using a large collection of songs generated by users of these platforms from May to October 2024. Using a combination of state-of-the-art text embedding models, dimensionality reduction and clustering methods, we analyze the prompts, tags and lyrics, and automatically annotate and display the processed data in interactive plots. Our results reveal prominent themes in lyrics, language preference, prompting strategies, as well as peculiar attempts at steering models through the use of metatags. To promote the musicological study of the developing cultural practice of AI-generated music we share our code and resources.
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