M6: Multi-generator, Multi-domain, Multi-lingual and cultural, Multi-genres, Multi-instrument Machine-Generated Music Detection Databases

TL;DR

The paper introduces M6, a comprehensive, diverse dataset for machine-generated music detection, addressing a critical need for robust benchmarks to improve detection methods and protect the value of human compositions.

Contribution

M6 is the first large-scale, multi-dimensional dataset for MGMD, covering multiple generators, domains, languages, cultures, genres, and instruments, facilitating advanced research.

Findings

Baseline models show significant room for improvement.

Diversity of M6 enhances robustness of MGMD research.

Data analysis reveals complexity in distinguishing MG from human music.

Abstract

Machine-generated music (MGM) has emerged as a powerful tool with applications in music therapy, personalised editing, and creative inspiration for the music community. However, its unregulated use threatens the entertainment, education, and arts sectors by diminishing the value of high-quality human compositions. Detecting machine-generated music (MGMD) is, therefore, critical to safeguarding these domains, yet the field lacks comprehensive datasets to support meaningful progress. To address this gap, we introduce \textbf{M6}, a large-scale benchmark dataset tailored for MGMD research. M6 is distinguished by its diversity, encompassing multiple generators, domains, languages, cultural contexts, genres, and instruments. We outline our methodology for data selection and collection, accompanied by detailed data analysis, providing all WAV form of music. Additionally, we provide baseline performance scores using foundational binary classification models, illustrating the complexity of MGMD and the significant room for improvement. By offering a robust and multifaceted resource, we aim to empower future research to develop more effective detection methods for MGM. We believe M6 will serve as a critical step toward addressing this societal challenge. The dataset and code will be freely available to support open collaboration and innovation in this field.