{"updated":"2025-01-19T19:09:54.727413+00:00","links":{},"id":207402,"created":"2025-01-19T01:09:06.983140+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00207402","sets":["1164:5064:10102:10386"]},"path":["10386"],"owner":"44499","recid":"207402","title":["大局的構造に基づく正則化を用いた自己注意機構付き深層ドラム採譜"],"pubdate":{"attribute_name":"公開日","attribute_value":"2020-10-26"},"_buckets":{"deposit":"a5f9f178-805f-4be3-97e7-3b3fb3199aa3"},"_deposit":{"id":"207402","pid":{"type":"depid","value":"207402","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"大局的構造に基づく正則化を用いた自己注意機構付き深層ドラム採譜","author_link":["517675","517673","517674","517676"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"大局的構造に基づく正則化を用いた自己注意機構付き深層ドラム採譜"}]},"item_type_id":"4","publish_date":"2020-10-26","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"},{"subitem_text_value":"京都大学大学院情報学研究科"}]},"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/207402/files/IPSJ-MUS20129003.pdf","label":"IPSJ-MUS20129003.pdf"},"date":[{"dateType":"Available","dateValue":"2022-10-26"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MUS20129003.pdf","filesize":[{"value":"1.0 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":"185d4742-027b-48e1-bf29-7b76cfe2d8c6","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2020 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"石塚, 崚斗"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"錦見, 亮"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"中村, 栄太"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"吉井, 和佳"}],"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":"本稿では，音響音楽信号からドラムのオンセット時刻をテイタム単位で推定する手法を述べる．自動ドラム採譜では，フレーム単位で設計された深層ニューラルネットワーク (deep neural network ; DNN) により，スペクトログラムを入力としてドラムのオンセット時刻を出力する手法が盛んに研究されてきたが，記号単位でドラム譜の推定を行う研究はまだ少ない．フレーム単位の入力からテイタム単位の出力を行う機構 (採譜モデル) として，エンコーダ・デコーダモデルがある．しかし，DNN の学習に用いるペアデータの量が限られているために，採譜モデルが音楽的に不自然なドラムパターンを生成してしまうという問題点が残されている．このような背景から，我々はフレーム単位の入力特徴量からテイタム単位のドラム譜を推定する採譜モデルを設計する．さらに，採譜モデルの推定結果を音楽的に妥当なパターンに誘導するため，大規模ドラム譜データを用いて学習した言語モデルによる評価値を，採譜モデルの学習時に正則化項として組み込む手法を提案する．このとき，採譜モデルに自己注意機構を導入し，言語モデルに Masked language model (MLM) を利用することで，双方向の文脈から楽曲の長期的な構造を学習することができる．標準データセットを用いた実験により，提案法の効果を示す．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告音楽情報科学（MUS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2020-10-26","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"3","bibliographicVolumeNumber":"2020-MUS-129"}]},"relation_version_is_last":true,"weko_creator_id":"44499"}}