{"id":210265,"created":"2025-01-19T01:11:31.282491+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00210265","sets":["1164:5336:10549:10550"]},"path":["10550"],"owner":"44499","recid":"210265","title":["歌唱テクニックの識別におけるhand-cratfted特徴量と深層学習抽出特徴量の比較"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-03-09"},"_buckets":{"deposit":"a5d39f8f-c9ed-4923-a101-773736e8aeec"},"_deposit":{"id":"210265","pid":{"type":"depid","value":"210265","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"歌唱テクニックの識別におけるhand-cratfted特徴量と深層学習抽出特徴量の比較","author_link":["531827","531830","531828","531829"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"歌唱テクニックの識別におけるhand-cratfted特徴量と深層学習抽出特徴量の比較"},{"subitem_title":"A Comparison of Hand-crafted Feature and Deep-extracted Feature on Singing Technique Classification","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2021-03-09","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"筑波大学"},{"subitem_text_value":"KAIST"},{"subitem_text_value":"筑波大学"},{"subitem_text_value":"筑波大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"KAIST","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/210265/files/IPSJ-EC21059030.pdf","label":"IPSJ-EC21059030.pdf"},"date":[{"dateType":"Available","dateValue":"2023-03-09"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-EC21059030.pdf","filesize":[{"value":"2.6 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":"40"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"41b2cf1c-635e-40c4-ab21-9211d89f101a","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":"山本, 雄也"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Juhan, Nam"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"寺澤, 洋子"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"平賀, 譲"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12049625","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":"2188-8914","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"本研究は歌唱テクニックの識別において，専門知識に基づき設計された特徴量（hand-crafted 特徴量）と深層学習によって自律的に獲得した特徴量の識別性能を比較するものである．歌唱テクニックは歌手が歌唱中に音高・音色・音量を変動させることにより表現する技法である．歌唱テクニックの様相は様々であり，中には特性が未解明なものや非自明なものも含まれているため，その特徴をとらえるのは難しい．本研究では深層学習による自律的な特徴獲得によって，歌唱テクニックの明示的モデリングを回避する方法について検討する．検証事項として特徴抽出の良し悪しのみを考えるため，分類器の条件を一定にする．従来の音声分類問題に用いられた hand-crafted 特徴量と深層学習により抽出した特徴量を用いて同分類器を学習させ比較する．10 種類の歌唱テクニック分類実験の結果，深層学習による特徴抽出では 73.6% の正解率が得られた．この数値は hand-crafted 特徴量での結果を 2.6% 上回っており，明示的モデリングなしでも hand-crafted 特徴量を用いた場合と同等の性能が得られることを確認した．特に極端な歌唱テクニックにおいて hand-crafted 特徴量を用いた場合より正解率が高く，深層学習による特徴の自動獲得が有用である可能性を示した．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"5","bibliographic_titles":[{"bibliographic_title":"研究報告エンタテインメントコンピューティング（EC）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2021-03-09","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"30","bibliographicVolumeNumber":"2021-EC-59"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"updated":"2025-01-19T18:12:38.091021+00:00","links":{}}