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Melody2Vec: Distributed Representations of Melodic Phrases based on Melody Segmentation
https://ipsj.ixsq.nii.ac.jp/records/195411
https://ipsj.ixsq.nii.ac.jp/records/1954115241a95f-2c67-4b79-8d1f-805dbe763346
| 名前 / ファイル | ライセンス | アクション |
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IPSJ-JNL6003023.pdf (2.4 MB)
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Copyright (c) 2019 by the Information Processing Society of Japan
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| オープンアクセス | ||
| Item type | Journal(1) | |||||||||
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| 公開日 | 2019-03-15 | |||||||||
| タイトル | ||||||||||
| タイトル | Melody2Vec: Distributed Representations of Melodic Phrases based on Melody Segmentation | |||||||||
| タイトル | ||||||||||
| 言語 | en | |||||||||
| タイトル | Melody2Vec: Distributed Representations of Melodic Phrases based on Melody Segmentation | |||||||||
| 言語 | ||||||||||
| 言語 | eng | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | [特集：若手研究者] melody processing, distributed representations, word2vec, melody retrieval | |||||||||
| 資源タイプ | ||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||
| 資源タイプ | journal article | |||||||||
| 著者所属 | ||||||||||
| Faculty of Global Media Studies, Komazawa University | ||||||||||
| 著者所属 | ||||||||||
| Future University Hakodate | ||||||||||
| 著者所属(英) | ||||||||||
| en | ||||||||||
| Faculty of Global Media Studies, Komazawa University | ||||||||||
| 著者所属(英) | ||||||||||
| en | ||||||||||
| Future University Hakodate | ||||||||||
| 著者名 |
Tatsunori, Hirai
× Tatsunori, Hirai
× Shun, Sawada
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| 著者名(英) |
Tatsunori, Hirai
× Tatsunori, Hirai
× Shun, Sawada
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| 論文抄録 | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | In this paper, we present melody2vec, an extension of the word2vec framework to melodies. To apply the word2vec framework to a melody, a definition of a word within a melody is required. We assume phrases within melodies to be words and acquire these words via melody segmentation applying rules for grouping musical notes called Grouping Preference Rules (GPR) in the Generative Theory of Tonal Music (GTTM). We employed a skip-gram representation to train our model using 10,853 melody tracks extracted from MIDI files primarily constructed from pop music. Experimental results show the effectiveness of our model in representing the semantic relatedness between melodic phrases. In addition, we propose a method to edit melodies by replacing melodic phrases within a musical piece based on the similarity of the phrase vectors. The naturalness of the resulting melody was evaluated via a user study and most participants who did not know the musical piece could not point out where the melody had been replaced. ------------------------------ This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.27(2019) (online) DOI http://dx.doi.org/10.2197/ipsjjip.27.278 ------------------------------ |
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| 論文抄録(英) | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | In this paper, we present melody2vec, an extension of the word2vec framework to melodies. To apply the word2vec framework to a melody, a definition of a word within a melody is required. We assume phrases within melodies to be words and acquire these words via melody segmentation applying rules for grouping musical notes called Grouping Preference Rules (GPR) in the Generative Theory of Tonal Music (GTTM). We employed a skip-gram representation to train our model using 10,853 melody tracks extracted from MIDI files primarily constructed from pop music. Experimental results show the effectiveness of our model in representing the semantic relatedness between melodic phrases. In addition, we propose a method to edit melodies by replacing melodic phrases within a musical piece based on the similarity of the phrase vectors. The naturalness of the resulting melody was evaluated via a user study and most participants who did not know the musical piece could not point out where the melody had been replaced. ------------------------------ This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.27(2019) (online) DOI http://dx.doi.org/10.2197/ipsjjip.27.278 ------------------------------ |
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| 書誌レコードID | ||||||||||
| 収録物識別子タイプ | NCID | |||||||||
| 収録物識別子 | AN00116647 | |||||||||
| 書誌情報 |
情報処理学会論文誌 巻 60, 号 3, 発行日 2019-03-15 |
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| ISSN | ||||||||||
| 収録物識別子タイプ | ISSN | |||||||||
| 収録物識別子 | 1882-7764 | |||||||||
