{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00230038","sets":["6504:11436:11440"]},"path":["11440"],"owner":"44499","recid":"230038","title":["小規模データセットでの楽曲生成におけるLSTMとTransformerの比較"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"9e861efa-229c-491b-89b6-8087751490fa"},"_deposit":{"id":"230038","pid":{"type":"depid","value":"230038","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"小規模データセットでの楽曲生成におけるLSTMとTransformerの比較","author_link":["618895","618894"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"小規模データセットでの楽曲生成におけるLSTMとTransformerの比較"}]},"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":"2023-02-16","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":"工学院大"},{"subitem_text_value":"工学院大"}]},"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/230038/files/IPSJ-Z85-1T-03.pdf","label":"IPSJ-Z85-1T-03.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-1T-03.pdf","filesize":[{"value":"1.0 MB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"fe266328-454a-4bb3-99ae-308adf267b14","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"千羽, 雄樹"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"小林, 亜樹"}],"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":"自動楽曲生成モデルにおいて2019 年に Google が発表した、自身が開発した ディープニューラルネットワークモデル の「Transformer」を利用した自動楽曲生成プログラム「Music Transformer」により、以前にはできなかった「フレーズの繰り返し」、「フレーズの終わりの自然さ」などの表現が可能になった。本研究では限られた小規模のデータセットで学習を行い楽曲を生成すると、Transformerが表現できるようになった特徴が出現するのか、これまでメジャーだった自動楽曲生成モデルよりも好まれる楽曲が生成されるのかを、Transformer発表前に主に使われていた自動楽曲生成モデルである「LSTM」と比較する。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"488","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"487","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":230038,"updated":"2025-01-19T11:18:54.173612+00:00","links":{},"created":"2025-01-19T01:29:33.569172+00:00"}