{"created":"2025-01-19T01:12:40.118562+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00211521","sets":["1164:5064:10547:10607"]},"path":["10607"],"owner":"44499","recid":"211521","title":["コード進行によるヒット曲予測システムの構築"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-06-11"},"_buckets":{"deposit":"5592e3ea-d785-4823-898c-2d2d0d5916ba"},"_deposit":{"id":"211521","pid":{"type":"depid","value":"211521","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"コード進行によるヒット曲予測システムの構築","author_link":["537477","537476","537475","537474"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"コード進行によるヒット曲予測システムの構築"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"一般発表","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2021-06-11","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"兵庫県立姫路西高等学校"},{"subitem_text_value":"兵庫県立姫路西高等学校"},{"subitem_text_value":"国立研究開発法人産業技術総合研究所"},{"subitem_text_value":"兵庫県立姫路西高等学校"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Hyogo Prefecture Himeji Nishi Senior High School","subitem_text_language":"en"},{"subitem_text_value":"Hyogo Prefecture Himeji Nishi Senior High School","subitem_text_language":"en"},{"subitem_text_value":"National Institute of Advanced Industrial Science and Technology (AIST)","subitem_text_language":"en"},{"subitem_text_value":"Hyogo Prefecture Himeji Nishi Senior High School","subitem_text_language":"en"}]},"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/211521/files/IPSJ-MUS21131012.pdf","label":"IPSJ-MUS21131012.pdf"},"date":[{"dateType":"Available","dateValue":"2023-06-11"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MUS21131012.pdf","filesize":[{"value":"1.7 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":"f8167701-5488-4846-a7b5-044b8c59b4cc","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"吉田, 隼輔"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"木村, 優介"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"深山, 覚"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"林, 宏樹"}],"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":"本研究では，楽曲のコード進行からヒット曲の分析を行い，そこから楽曲がヒットするかを算出する予測モデルを構築する．具体的には Billboard Japan Year End Hot 100 の 2010 年から 2019 年の上位 20 曲のサビ部分のコード進行を用い，3 つの分析を行って予測をした．一つ目の分析では，ダイアトニックコード，繰り返し，コードの種類に着目し，コード進行の複雑性を分析した．二つ目の分析では，tf-idf を用いてコード進行のパターンを分析した．三つ目の分析では，潜在ディリクレ配分法を用いて特徴的なコード進行を分析した．これらの分析結果を数値化したものを入力として，重回帰分析とニューラルネットワークによって楽曲のランキングを予測するシステムを構築した．その後 2020 年の楽曲のコード進行を入力してランキングを予測し，実際のランキングと比較することで予測の性能を確認した．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"5","bibliographic_titles":[{"bibliographic_title":"研究報告音楽情報科学（MUS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2021-06-11","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"12","bibliographicVolumeNumber":"2021-MUS-131"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":211521,"updated":"2025-01-19T17:46:18.375974+00:00","links":{}}