{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00218438","sets":["1164:5064:10822:10948"]},"path":["10948"],"owner":"44499","recid":"218438","title":["各楽器音に着目した楽曲間類似度学習"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-06-10"},"_buckets":{"deposit":"514a3223-a8b8-4b12-99eb-22b9a81f8d24"},"_deposit":{"id":"218438","pid":{"type":"depid","value":"218438","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"各楽器音に着目した楽曲間類似度学習","author_link":["567985","567986","567984"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"各楽器音に着目した楽曲間類似度学習"},{"subitem_title":"Music similarity learning focusing on individual instrumental sounds","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ポスターセッション3","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2022-06-10","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"名古屋大学情報学研究科"},{"subitem_text_value":"名古屋大学情報基板センター"},{"subitem_text_value":"名古屋大学情報基板センター"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/218438/files/IPSJ-MUS22134046.pdf","label":"IPSJ-MUS22134046.pdf"},"date":[{"dateType":"Available","dateValue":"2024-06-10"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MUS22134046.pdf","filesize":[{"value":"2.4 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"21"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"54b89af5-61a2-45e4-8b5a-57343aaabc16","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"橋爪, 優果"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"李, 莉"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"戸田, 智基"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10438388","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8752","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"自由度の高い楽曲推薦・検索を実現するためには，楽曲間類似度を計算する必要があり，その基準が重要となる．楽曲信号に対して楽曲間類似度を直接計算する枠組みとして，各楽曲のタグ情報を用いて，トリプレット損失に基づく距離学習を行うデータ駆動型の手法が提案されている．しかし，その結果得られる楽曲間類似度の基準は，様々な楽器音が混ざった楽曲全体を捉える場合が多く，例えば，類似したドラム音を含む楽曲を検索するといったことが困難であり，楽曲推薦・検索システムの機能が限定される．そこで，本報告では，より自由度の高い楽曲推薦・検索システムの実現のために，楽曲中の各楽器音に着目した楽曲間類似度計算を提案する．提案手法では，タグ情報を用いずに個別の楽器音に対して距離学習を行う．さらに，実際には各楽器音源が常に得られるとは限らないことを想定し，楽器音源分離で得られる各楽器音源を用いて距離学習を行う効果も検討する．実験の結果，(1) 各楽器音に対して異なる類似度の基準を学習できること，(2) 一部の楽器音を用いて学習した類似度は，楽曲そのものを用いて学習したものよりも正確な結果を導くことが可能なこと，(3) 分離した楽器音源を用いて学習すると性能が低下すること，(4) 提案手法で学習した類似度の基準は人間の感覚に対応する結果を示すことが明らかとなった．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"The criteria for measuring music similarity are important for developing a flexible music recommendation system. Some data-driven methods have been proposed to calculate music similarity from only music signals, such as metric learning based on a triplet loss using tag information on each musical piece. However, the resulting music similarity metric usually captures the entire piece of music, i.e., the mixing of various instrumental sound sources, limiting the capability of the music recommendation system, e.g., it is difficult to search for a musical piece containing similar drum sounds. Besides, for greater accuracy, the tag information is commonly labeled manually, but this requires a lot of human resources and time. Towards the development of a more flexible music recommendation system, we propose a music similarity calculation method that focuses on individual instrumental sound sources in a musical piece. We adopt metric learning to individual instrumental sound source signals without using any tag information. Furthermore, we also investigate the effects of using instrumental sound source separation to obtain each source in the proposed method since each instrumental sound source is not always available in practice. Experimental results have shown that (1) different similarity metrics can be learned for individual instrumental sound sources, (2) similarity metrics learned using some instrumental sound sources can lead to more accurate results than that learned using the entire piece of music, (3) the performance degrades when training a network with the separated instrumental sounds, and (4) similarity metrics learned by the proposed method well produce results that correspond to perception by human senses.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告音楽情報科学（MUS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-06-10","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"46","bibliographicVolumeNumber":"2022-MUS-134"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":218438,"updated":"2025-01-19T15:09:42.712148+00:00","links":{},"created":"2025-01-19T01:18:48.477920+00:00"}