{"created":"2025-01-19T01:37:51.301528+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00236026","sets":["6504:11678:11689"]},"path":["11689"],"owner":"44499","recid":"236026","title":["アノテータごとのばらつきを考慮した音響イベント検出"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-03-01"},"_buckets":{"deposit":"70a27cfe-cd20-4d74-91c4-3c5a27ab7f5f"},"_deposit":{"id":"236026","pid":{"type":"depid","value":"236026","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"アノテータごとのばらつきを考慮した音響イベント検出","author_link":["645024","645025","645026"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"アノテータごとのばらつきを考慮した音響イベント検出"}]},"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":"2024-03-01","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":"同志社大 / 産総研"},{"subitem_text_value":"産総研"},{"subitem_text_value":"同志社大 / 産総研"}]},"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/236026/files/IPSJ-Z86-1R-07.pdf","label":"IPSJ-Z86-1R-07.pdf"},"date":[{"dateType":"Available","dateValue":"2024-07-03"}],"format":"application/pdf","filename":"IPSJ-Z86-1R-07.pdf","filesize":[{"value":"546.0 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"eb41467a-6a1d-4a6a-82d3-b0d99d5abb9e","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"古賀, 直樹"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"坂東, 宜昭"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"井本, 桂右"}],"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，複数のアノテータが作成したばらつきのあるラベルを用いた音響イベント検出 (SED) について述べる．音響イベントの開始・終了時刻と種類を推定するSEDでは，教師データの品質がモデルの性能に直結するが，イベントの開始・終了時刻は主観的なためアノテータによってラベルがばらつく．そこで本研究では，アノテータの違いを陽にモデルに組み込んだ Crowd Layer をSEDの推論モデル CNN-BiGRU に導入することで，本問題に対処する．複数人のアノテータによる30時間の実録音データセットを構築し，提案法の有効性を評価した．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"368","bibliographic_titles":[{"bibliographic_title":"第86回全国大会講演論文集"}],"bibliographicPageStart":"367","bibliographicIssueDates":{"bibliographicIssueDate":"2024-03-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2024"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":236026,"updated":"2025-01-19T09:25:27.639961+00:00","links":{}}