{"links":{},"id":180839,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00180839","sets":["6504:9168:9182"]},"path":["9182"],"owner":"6748","recid":"180839","title":["LSTMによる音楽音響信号の修復法の提案-周波数フィルタ導入による学習データ量削減の検討-"],"pubdate":{"attribute_name":"公開日","attribute_value":"2017-03-16"},"_buckets":{"deposit":"3908c62e-fdad-4b53-a052-3900c5b24c2f"},"_deposit":{"id":"180839","pid":{"type":"depid","value":"180839","revision_id":0},"owners":[6748],"status":"published","created_by":6748},"item_title":"LSTMによる音楽音響信号の修復法の提案-周波数フィルタ導入による学習データ量削減の検討-","author_link":["391038","391039","391036","391037"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"LSTMによる音楽音響信号の修復法の提案-周波数フィルタ導入による学習データ量削減の検討-"}]},"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":"2017-03-16","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":"東工大"},{"subitem_text_value":"東工大"},{"subitem_text_value":"東工大"},{"subitem_text_value":"東工大/ホンダRIJ"}]},"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/180839/files/IPSJ-Z79-7L-06.pdf","label":"IPSJ-Z79-7L-06.pdf"},"date":[{"dateType":"Available","dateValue":"2017-05-22"}],"format":"application/pdf","filename":"IPSJ-Z79-7L-06.pdf","filesize":[{"value":"1.3 MB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"8946b6c9-1f92-40ef-b627-91e8c10b7850","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2017 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"谷口, 亮輔"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"小島, 諒介"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"干場, 功太郎"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"中臺, 一博"}],"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":"本稿では、深層学習の一手法であるLSTM を用いた音楽音響信号修復について報告する．一般に，深層学習では性能の高いモデルを学習するために大量のデータが必要である．実際に音楽音響信号修復に深層学習を用いると,学習データが少ない場合，情報が比較的スパースである高域の修復性能が劣化するという問題が発生する．この問題を解決するため，学習時に，入力信号に対して，周波数フィルタを用いることにより，周波数方向に重みをかけることを提案する．予備検討の結果，少量の学習データであっても提案法が有効であることを確認した．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"134","bibliographic_titles":[{"bibliographic_title":"第79回全国大会講演論文集"}],"bibliographicPageStart":"133","bibliographicIssueDates":{"bibliographicIssueDate":"2017-03-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2017"}]},"relation_version_is_last":true,"weko_creator_id":"6748"},"created":"2025-01-19T00:48:38.859388+00:00","updated":"2025-01-20T04:39:18.620053+00:00"}