Data-Driven Analysis of Text-Conditioned AI-Generated Music: A Case Study with Suno and Udio

Fuente: arXiv
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Auteurs principaux: Casini, Luca, Vila, Laura Cros, Dalmazzo, David, Kaila, Anna-Kaisa, Sturm, Bob L. T.
Format: Preprint
Publié: 2025
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author Casini, Luca
Vila, Laura Cros
Dalmazzo, David
Kaila, Anna-Kaisa
Sturm, Bob L. T.
author_facet Casini, Luca
Vila, Laura Cros
Dalmazzo, David
Kaila, Anna-Kaisa
Sturm, Bob L. T.
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2509_11824
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Data-Driven Analysis of Text-Conditioned AI-Generated Music: A Case Study with Suno and Udio
Casini, Luca
Vila, Laura Cros
Dalmazzo, David
Kaila, Anna-Kaisa
Sturm, Bob L. T.
Information Retrieval
Artificial Intelligence
Machine Learning
Sound
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.
title Data-Driven Analysis of Text-Conditioned AI-Generated Music: A Case Study with Suno and Udio
topic Information Retrieval
Artificial Intelligence
Machine Learning
Sound
url https://arxiv.org/abs/2509.11824