| Presentation | 2022-03-03 A study on hit classification by machine learning of Japanese popular music using Spotify Audio Features Kengo Kitamura, Susumu Kuroyanagi, |
|---|---|
| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | It is assumed that hit songs have common features with respect to the characteristics of hit songs. Based on this assumption, researches have been conducted to predict hit songs using machine learning. Most of them have been conducted for Western music. Therefore, in this study, we verify that it is possible to classify Japanese music into hit songs and other songs. In addition to song classification, we also examine hit song prediction, which is a classification method using past song data, test data, and future songs as training data. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Spotify Audio Features / Support Vector Machine / SOM / Machine Learning |
| Paper # | NC2021-67 |
| Date of Issue | 2022-02-23 (NC) |
| Conference Information | |
| Committee | MBE / NC |
|---|---|
| Conference Date | 2022/3/2(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Ryuhei Okuno(Setsunan Univ.) / Rieko Osu(Waseda Univ.) |
| Vice Chair | Junichi Hori(Niigata Univ.) / Hiroshi Yamakawa(Univ of Tokyo) |
| Secretary | Junichi Hori(Osaka Electro-Communication Univ) / Hiroshi Yamakawa(ATR) |
| Assistant | Jun Akazawa(Meiji Univ. of Integrative Medicine) / Emi Yuda(Tohoku Univ) / Nobuhiko Wagatsuma(Toho Univ.) / Tomoki Kurikawa(KMU) |
| Paper Information | |
| Registration To | Technical Committee on ME and Bio Cybernetics / Technical Committee on Neurocomputing |
|---|---|
| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A study on hit classification by machine learning of Japanese popular music using Spotify Audio Features |
| Sub Title (in English) | |
| Keyword(1) | Spotify Audio Features |
| Keyword(2) | Support Vector Machine |
| Keyword(3) | SOM |
| Keyword(4) | Machine Learning |
| 1st Author's Name | Kengo Kitamura |
| 1st Author's Affiliation | Nagoya Institute of Technology(NIT) |
| 2nd Author's Name | Susumu Kuroyanagi |
| 2nd Author's Affiliation | Nagoya Institute of Technology(NIT) |
| Date | 2022-03-03 |
| Paper # | NC2021-67 |
| Volume (vol) | vol.121 |
| Number (no) | NC-390 |
| Page | pp.pp.112-117(NC), |
| #Pages | 6 |
| Date of Issue | 2022-02-23 (NC) |