{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00080385","sets":["1164:5159:6679:6680"]},"path":["6680"],"owner":"11","recid":"80385","title":["音響特徴・ベース音・和音遷移を用いた自動和音認識"],"pubdate":{"attribute_name":"公開日","attribute_value":"2012-01-27"},"_buckets":{"deposit":"2980baa4-be60-4fe0-b3a7-15a3d3a8083a"},"_deposit":{"id":"80385","pid":{"type":"depid","value":"80385","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"音響特徴・ベース音・和音遷移を用いた自動和音認識","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"音響特徴・ベース音・和音遷移を用いた自動和音認識"},{"subitem_title":"Automatic Chord Recognition Based on Probabilistic Integration of Acoustic Features, Bass Sounds, and Chord Transition","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"音楽の認識・理解","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2012-01-27","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"京都大学大学院情報学研究科"},{"subitem_text_value":"京都大学大学院情報学研究科"},{"subitem_text_value":"京都大学大学院情報学研究科"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Informatics, Kyoto University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Informatics, Kyoto University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Informatics, Kyoto University","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/80385/files/IPSJ-SLP12090029.pdf"},"date":[{"dateType":"Available","dateValue":"2014-01-27"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SLP12090029.pdf","filesize":[{"value":"444.4 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"22"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"3622cd44-7e62-4253-992a-4a6110844bae","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2012 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"糸山, 克寿"},{"creatorName":"尾形, 哲也"},{"creatorName":"奥乃, 博"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Katsutoshi, Itoyama","creatorNameLang":"en"},{"creatorName":"Tetsuya, Ogata","creatorNameLang":"en"},{"creatorName":"Hiroshi, G.Okuno","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10442647","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_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"本稿では，多重奏音楽音響信号に対する自動和音和音手法について述べる．和音の認識においては，音楽的要素の関連性を考慮することが重要である．我々は，和音を表現する音響特徴であるクロマベクトルに加えて和音と関わりの深い音楽的要素であるベース音を用いた自動和音認識手法を構築した．和音遷移のパターンを事前に階層 Pitman-Yor 言語モデルで学習し，Viterbi アルゴリズムに基づく最大事後確率推定で和音系列を推定する．Beatles の 150 楽曲を用いた評価実験で，本手法は 73.7% の認識率を達成した．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"This paper describes a method that identifies musical chords in polyphonic musical signals. As musical chords mainly represent the harmony of music and are related to other musical elements such as melody and rhythm, we should be able to recognize chords more effectively if this interrelationship is taken into consideration. We use bass pitches as clues for improving chord recognition. The proposed chord recognition system is constructed based on Viterbi-algorithm-based maximum a posteriori estimation that uses a posterior probability based on chord features, chord transition patterns, and bass pitch distributions. Experimental results with 150 Beatles songs that has keys and no modulation showed that the recognition rate was 73.7% on average.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"7","bibliographic_titles":[{"bibliographic_title":"研究報告音声言語情報処理（SLP）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2012-01-27","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"29","bibliographicVolumeNumber":"2012-SLP-90"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"id":80385,"updated":"2025-01-21T19:50:22.438499+00:00","links":{},"created":"2025-01-18T23:34:52.488252+00:00"}