{"created":"2025-01-19T01:20:49.292074+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00220794","sets":["6504:11035:11043"]},"path":["11043"],"owner":"44499","recid":"220794","title":["ドラムグルーヴ解析におけるLSTM変分オートエンコーダ利用の検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-02-17"},"_buckets":{"deposit":"e350753b-be9d-45b9-8fd4-f3b7ce33991a"},"_deposit":{"id":"220794","pid":{"type":"depid","value":"220794","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"ドラムグルーヴ解析におけるLSTM変分オートエンコーダ利用の検討","author_link":["577746","577745","577747","577744"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ドラムグルーヴ解析におけるLSTM変分オートエンコーダ利用の検討"}]},"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":"2022-02-17","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":"北海道科学大"},{"subitem_text_value":"北海道科学大"},{"subitem_text_value":"北海道科学大"},{"subitem_text_value":"北海道科学大"}]},"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/220794/files/IPSJ-Z84-5D-02.pdf","label":"IPSJ-Z84-5D-02.pdf"},"date":[{"dateType":"Available","dateValue":"2022-10-22"}],"format":"application/pdf","filename":"IPSJ-Z84-5D-02.pdf","filesize":[{"value":"610.0 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"c0426980-75b3-4f66-9fa6-5248777253f2","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"松川, 瞬"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"竹沢, 恵"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"稲垣, 潤"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"真田, 博文"}],"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":"近年の音楽体験においては，映像と音楽のリズムが合致して身体的高揚感＝グルーヴを得ることが重要となる．しかし，リズムの要となるドラムのグルーヴを，音楽要素（奏者に依存しない要素）と演奏特性（奏者に依存する要素）の両方を踏まえ，定量的に解明する研究は殆どない．本研究では，楽曲データを入力として，音楽要素と演奏特性を同時かつ定量的に表現する機械学習モデルを構築し，ドラムグルーヴをデータドリブンに解析することを目標とする．本稿では，LSTMの中間層出力をグルーヴの特徴と見做し，変分オートエンコーダによりその隠れ状態を分析・可視化することで，楽曲のグルーヴ感，特に演奏特性の差異の抽出・再構成を試みる．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"92","bibliographic_titles":[{"bibliographic_title":"第84回全国大会講演論文集"}],"bibliographicPageStart":"91","bibliographicIssueDates":{"bibliographicIssueDate":"2022-02-17","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2022"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"links":{},"id":220794,"updated":"2025-01-19T14:25:42.650343+00:00"}