{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00215097","sets":["6504:10735:10808"]},"path":["10808"],"owner":"44499","recid":"215097","title":["ALBERTおよびLSTMベースのモデルによる対話破綻検出"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-03-04"},"_buckets":{"deposit":"393c4c18-84d6-4a88-a9d5-689707f175e9"},"_deposit":{"id":"215097","pid":{"type":"depid","value":"215097","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"ALBERTおよびLSTMベースのモデルによる対話破綻検出","author_link":["553637","553639","553643","553638","553640","553644","553641","553642"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ALBERTおよびLSTMベースのモデルによる対話破綻検出"}]},"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":"2021-03-04","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":"東京都市大"},{"subitem_text_value":"早大"},{"subitem_text_value":"東京都市大"},{"subitem_text_value":"東京都市大"},{"subitem_text_value":"東京都市大"},{"subitem_text_value":"東京都市大"},{"subitem_text_value":"東京都市大"},{"subitem_text_value":"東京都市大"}]},"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/215097/files/IPSJ-Z83-6S-05.pdf","label":"IPSJ-Z83-6S-05.pdf"},"date":[{"dateType":"Available","dateValue":"2021-12-28"}],"format":"application/pdf","filename":"IPSJ-Z83-6S-05.pdf","filesize":[{"value":"316.9 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"5ec19963-a9c5-499f-a542-0cb44345183c","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"戎, 浡"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"曹, 婷"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"木村, 優平"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"片倉, 多智"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"早坂, 絵央"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"吉原, 圭祐"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"西村, 百之輔"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"延澤, 志保"}],"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":"品質の良い対話システムを開発するため，対話システムの発話内容の品質を確保することは重要であると考えられる．本研究では，雑談対話システムを対象として，ユーザとの会話の継続性の向上のため，システムの対話破綻検出の精度を向上させる方法を検討する．提案手法では，ALBERTを用いた事前学習と，LSTMを用いた深層学習による対話破綻検出のモデルとを用いる．DBDCデータセットで実験を行い，事前学習モデルALBERTを微調整することで，提案モデルはベースラインのパフォーマンスのモデルよりも優れていることが示された．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"602","bibliographic_titles":[{"bibliographic_title":"第83回全国大会講演論文集"}],"bibliographicPageStart":"601","bibliographicIssueDates":{"bibliographicIssueDate":"2021-03-04","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2021"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":215097,"updated":"2025-01-19T16:19:26.540779+00:00","links":{},"created":"2025-01-19T01:15:52.707717+00:00"}