音楽ジャンルの楽曲自動分類システムの開発

抄録

This research aims to use AI and machine learning to classify music genres and assist artists. By objectively analyzing their own music, artists can better understand the characteristics of their music and incorporate popular trends. They can also evaluate their own work, set goals, and drive continuous improvement. In this work, we use Music2vec as a method to convert music into vector representations for classification. The study plans to classify music by genre, country of origin of the artist, and songs that are popular in each country. Experiments using Music2vec and the GTZAN dataset achieved a classification accuracy of 62%, demonstrating the feasibility of classifying music genres. However, further research is needed to explore the subdivided genre taxonomy and the impact of the artist's country of origin on the taxonomy.