{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00214933","sets":["6504:10735:10808"]},"path":["10808"],"owner":"44499","recid":"214933","title":["ポピュラー音楽に対する難易度に応じた深層ピアノ編曲"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-03-04"},"_buckets":{"deposit":"411e2275-2acd-4287-b435-5d86240acdbe"},"_deposit":{"id":"214933","pid":{"type":"depid","value":"214933","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"ポピュラー音楽に対する難易度に応じた深層ピアノ編曲","author_link":["553162","553164","553161","553163"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ポピュラー音楽に対する難易度に応じた深層ピアノ編曲"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"人工知能と認知科学","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2021-03-04","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"京大"},{"subitem_text_value":"京大"},{"subitem_text_value":"京大"},{"subitem_text_value":"京大"}]},"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/214933/files/IPSJ-Z83-2P-03.pdf","label":"IPSJ-Z83-2P-03.pdf"},"date":[{"dateType":"Available","dateValue":"2021-12-28"}],"format":"application/pdf","filename":"IPSJ-Z83-2P-03.pdf","filesize":[{"value":"293.4 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"f0878ac9-82c9-4a7a-8983-c3e01d9be437","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"寺尾, 萌夢"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"石塚, 崚斗"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"錦見, 亮"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"吉井, 和佳"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"本稿では、ポピュラー音楽のバンド譜を、指定した難易度に合わせてピアノ演奏用に自動編曲する手法について述べる。最近、深層学習を用いて、音楽 (MIDIデータ) の生成や編曲、スタイル変換を行う研究が盛んになりつつあるが、出力結果の演奏難易度を制御しようとする試みはいまだ存在しない。本研究では、まず、ポピュラー音楽のバンド譜と、対応する難易度アノテーション付きのピアノ譜を収集し、バンド譜のメロディ・伴奏パートと、ピアノ譜の左右パートの関係について統計的に調査する。この結果に基づき、バンド譜に含まれる音符およびそれらをオクターブシフトした音符の集合に対し、マスク操作を施すことでピアノ譜が得られるという仮定をおき、バンド譜のメロディ・伴奏パートからマスクを推定する深層ニューラルネットワークを難易度条件付きで教師あり学習することを試みる。収集したペアデータを用いた交差検定により、提案手法の有用性を検証する。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"260","bibliographic_titles":[{"bibliographic_title":"第83回全国大会講演論文集"}],"bibliographicPageStart":"259","bibliographicIssueDates":{"bibliographicIssueDate":"2021-03-04","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2021"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":214933,"updated":"2025-01-19T16:24:02.924940+00:00","links":{},"created":"2025-01-19T01:15:43.408282+00:00"}