Research on AI Composition Recognition Based on Music Rules

TL;DR

This paper proposes a music-rule-based algorithm to distinguish between human-composed and AI-generated music by analyzing musical modes, aiding copyright enforcement and the development of AI music.

Contribution

It introduces a novel music-rule-identifying algorithm based on mode stability to differentiate AI-generated music from human compositions.

Findings

The algorithm successfully distinguishes datasets from different sources.

Experimental results validate the effectiveness of the mode stability analysis.

The method provides technological support for music copyright protection.

Abstract

The development of artificial intelligent composition has resulted in the increasing popularity of machine-generated pieces, with frequent copyright disputes consequently emerging. There is an insufficient amount of research on the judgement of artificial and machine-generated works; the creation of a method to identify and distinguish these works is of particular importance. Starting from the essence of the music, the article constructs a music-rule-identifying algorithm through extracting modes, which will identify the stability of the mode of machine-generated music, to judge whether it is artificial intelligent. The evaluation datasets used are provided by the Conference on Sound and Music Technology(CSMT). Experimental results demonstrate the algorithm to have a successful distinguishing ability between datasets with different source distributions. The algorithm will also provide some technological reference to the benign development of the music copyright and artificial intelligent music.