IdolSongsJp Corpus: A Multi-Singer Song Corpus in the Style of Japanese Idol Groups
Hitoshi Suda, Junya Koguchi, Shunsuke Yoshida, Tomohiko Nakamura, Satoru Fukayama, Jun Ogata

TL;DR
The paper introduces IdolSongsJp, a comprehensive multi-singer song corpus in the style of Japanese idol groups, designed to benchmark music processing techniques with diverse, annotated tracks.
Contribution
It presents a newly created, annotated music corpus tailored for benchmarking various music information processing tasks involving idol group-style songs.
Findings
Corpus includes 15 professionally composed tracks with stems and annotations.
Demonstrates the corpus's diversity by comparing with real idol group songs.
Evaluates music processing techniques using the corpus.
Abstract
Japanese idol groups, comprising performers known as "idols," are an indispensable part of Japanese pop culture. They frequently appear in live concerts and television programs, entertaining audiences with their singing and dancing. Similar to other J-pop songs, idol group music covers a wide range of styles, with various types of chord progressions and instrumental arrangements. These tracks often feature numerous instruments and employ complex mastering techniques, resulting in high signal loudness. Additionally, most songs include a song division (utawari) structure, in which members alternate between singing solos and performing together. Hence, these songs are well-suited for benchmarking various music information processing techniques such as singer diarization, music source separation, and automatic chord estimation under challenging conditions. Focusing on these characteristics,…
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Taxonomy
TopicsAsian Culture and Media Studies · Music and Audio Processing · Artificial Intelligence in Games
