{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00215095","sets":["6504:10735:10808"]},"path":["10808"],"owner":"44499","recid":"215095","title":["SANOVA RNN: 低頻度な対話行為の特徴を考慮する対話行為推定モデル"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-03-04"},"_buckets":{"deposit":"5a1ecdec-7a40-425e-b506-875eab421847"},"_deposit":{"id":"215095","pid":{"type":"depid","value":"215095","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"SANOVA RNN: 低頻度な対話行為の特徴を考慮する対話行為推定モデル","author_link":["553628","553629"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"SANOVA RNN: 低頻度な対話行為の特徴を考慮する対話行為推定モデル"}]},"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":"名工大"},{"subitem_text_value":"名工大"}]},"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/215095/files/IPSJ-Z83-6S-03.pdf","label":"IPSJ-Z83-6S-03.pdf"},"date":[{"dateType":"Available","dateValue":"2021-12-28"}],"format":"application/pdf","filename":"IPSJ-Z83-6S-03.pdf","filesize":[{"value":"426.5 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"542ab31b-95f4-4bcc-bc31-b34d0d0e178b","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":"泉, 春乃"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"加藤, 昇平"}],"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":"雑談対話において，話者の発話の意図を示す対話行為は出現頻度に偏りが生じる．多くの対話行為推定モデルは出現頻度の高い対話行為に偏って推定する問題があるため，本稿では出現頻度の低い対話行為の特徴をよく捉えるためのネットワークであるSelf-Attention Networks One-Versus-All RNNを提案する．実験において，まず発話の分かち書き手法および分散表現の違いによる対話行為推定性能を比較した．またSANOVA RNNの対話行為推定性能を他手法と比較することで，SANOVA RNNは出現頻度の低い対話行為の特徴をよく捉えながら，対話全体でも高い推定性能を持つことを確認した．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"598","bibliographic_titles":[{"bibliographic_title":"第83回全国大会講演論文集"}],"bibliographicPageStart":"597","bibliographicIssueDates":{"bibliographicIssueDate":"2021-03-04","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2021"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":215095,"updated":"2025-01-19T16:19:30.566799+00:00","links":{},"created":"2025-01-19T01:15:52.596536+00:00"}