{"id":220293,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00220293","sets":["1164:5336:10887:11018"]},"path":["11018"],"owner":"44499","recid":"220293","title":["機械学習に基づく自然なエージェント動作の生成"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-09-29"},"_buckets":{"deposit":"9d1f7eff-1a1a-401e-9e61-33eeea803e6d"},"_deposit":{"id":"220293","pid":{"type":"depid","value":"220293","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"機械学習に基づく自然なエージェント動作の生成","author_link":["575907","575908","575906"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"機械学習に基づく自然なエージェント動作の生成"},{"subitem_title":"Generation of natural agent behavior based on machine learning","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"機械学習","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2022-09-29","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"京都大学情報学研究科"},{"subitem_text_value":"京都大学情報学研究科"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Kyoto University","subitem_text_language":"en"},{"subitem_text_value":"Kyoto University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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/220293/files/IPSJ-EC22065029.pdf","label":"IPSJ-EC22065029.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-EC22065029.pdf","filesize":[{"value":"3.2 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"40"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"e6013c1b-a410-4f58-98b2-744452c998af","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG."}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"宮澤, 恒光"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"中澤, 篤志"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Generation, of natural agent behavior based on machine learning","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12049625","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8914","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"アバター（エージェント）が様々な場面で利用され始めているのに従い，より人間らしい動作を行うエージェントが求められている．本研究では様々な機械学習モデルに人間同士の対話中の動作を学習させ，そのモデルを用いて動作生成を行い，モデルの有効性の評価を行った．具体的には，被験者 2 人に対話させる実験を行い，被験者の注視状態と発話に関する時系列データを獲得した．それをデータセットとして HMM, Transformer に基づいたモデルを学習させた．次に，学習させたモデルを用いてエージェントの対話行動を生成し，ゲームエンジンを用いて対話シーンを再現，生成結果の自然さやリアリティーに対する主観評価を行った．その結果，Transformer に基づいたモデルが柔軟に行動選択できることを示した．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"As avatars (agents) are beginning to be used in various situations, there is a demand for agents that perform more human-like actions. In this study, we trained various machine-learning models to perform human-like actions in conversations, generated actions using the models, and evaluated the effectiveness of the models. Specifically, we conducted experiments in which two subjects talked with each other and obtained time-series data about the subjects' gazing states and utterances. Using this dataset, we trained models based on HMM and Transformer. Next, we generated behavior of agents in conversations using the learned model, reproduced conversation scenes using a game engine, and subjectively evaluated the naturalness and reality of the generated results. The results showed that the model based on the Transformer can flexibly select actions.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"5","bibliographic_titles":[{"bibliographic_title":"研究報告エンタテインメントコンピューティング（EC）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-09-29","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"29","bibliographicVolumeNumber":"2022-EC-65"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"updated":"2025-01-19T14:36:53.271281+00:00","created":"2025-01-19T01:20:20.319955+00:00","links":{}}