{"created":"2025-01-19T01:29:19.147320+00:00","updated":"2025-01-19T11:22:35.693992+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00229887","sets":["6504:11436:11440"]},"path":["11440"],"owner":"44499","recid":"229887","title":["マルチモーダル対話におけるユーザごとの心象推定のための学習データの割当て"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"17c2662b-79b6-4550-975f-925744e91d47"},"_deposit":{"id":"229887","pid":{"type":"depid","value":"229887","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"マルチモーダル対話におけるユーザごとの心象推定のための学習データの割当て","author_link":["618406","618407","618408","618409"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"マルチモーダル対話におけるユーザごとの心象推定のための学習データの割当て"}]},"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":"2023-02-16","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":"阪大"},{"subitem_text_value":"阪大"},{"subitem_text_value":"阪大"},{"subitem_text_value":"阪大"}]},"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/229887/files/IPSJ-Z85-7P-06.pdf","label":"IPSJ-Z85-7P-06.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-7P-06.pdf","filesize":[{"value":"299.0 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"5d7c9ae1-38e1-4f13-92fc-be76c6452d2f","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"久保, 裕之輔"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"羅, 兆傑"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"武田, 龍"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"駒谷, 和範"}],"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":"ユーザの心象を対話システムが推定できれば，それに適応した応答が可能となる．機械学習は一般にデータの一様性を仮定しているが，実際にはユーザは多様であるため，全てを学習データとすると心象推定の性能低下につながる．本研究では，マルチモーダル対話において，個々のユーザに対して適切な学習データ集合を設定することで心象推定の性能向上を図る．まず，テストデータの心象推定の性能が上限となるユーザ単位の学習データ集合を，事前調査として得る．この集合内のユーザを近くに配置可能な距離尺度を設定し，ユーザのクラスタリングなどにより，性能が向上する学習データ集合を得る．これによって，心象推定の性能向上を確認する．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"176","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"175","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":229887,"links":{}}