{"id":216895,"updated":"2025-01-19T15:41:42.386518+00:00","links":{},"created":"2025-01-19T01:17:24.456344+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00216895","sets":["1164:4402:10858:10880"]},"path":["10880"],"owner":"44499","recid":"216895","title":["マルチモーダルデータを用いたオンラインミーティング参加者の感情推定"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-03-03"},"_buckets":{"deposit":"cf58ed02-819e-4e1d-9d41-1d5b823002b8"},"_deposit":{"id":"216895","pid":{"type":"depid","value":"216895","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"マルチモーダルデータを用いたオンラインミーティング参加者の感情推定","author_link":["560842","560840","560838","560839","560837","560841"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"マルチモーダルデータを用いたオンラインミーティング参加者の感情推定"},{"subitem_title":"Estimating Emotions of Participants in Online Meeting using Multimodal Data","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"セッション1","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2022-03-03","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"奈良先端科学技術大学院大学"},{"subitem_text_value":"大阪市立大学"},{"subitem_text_value":"奈良先端科学技術大学院大学／理化学研究所"},{"subitem_text_value":"日本大学"},{"subitem_text_value":"東京電機大学"},{"subitem_text_value":"奈良先端科学技術大学院大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Nara Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":"Osaka City University","subitem_text_language":"en"},{"subitem_text_value":"Nara Institute of Science and Technology / RIKEN","subitem_text_language":"en"},{"subitem_text_value":"Nihon University","subitem_text_language":"en"},{"subitem_text_value":"Tokyo Denki University","subitem_text_language":"en"},{"subitem_text_value":"Nara Institute of Science and Technology","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/216895/files/IPSJ-ICS22206002.pdf","label":"IPSJ-ICS22206002.pdf"},"date":[{"dateType":"Available","dateValue":"2024-03-03"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-ICS22206002.pdf","filesize":[{"value":"1.7 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の影響で，労働者がテレワークが取り入れられるようになり，上司や産業医にとってテレワーク中の労働者の心理状態は把握しにくい．我々は費用と労力，感染リスクを減らせるメリットがあるオンラインミーティングサービスに着目し，オンラインミーティングで得られる動画や音声などのマルチモーダルデータを用いて労働者の感情を推定する手法を検討する．オンラインミーティングサービスを用いてグループディスカッションを被験者にしてもらい，そこから映像，心拍など様々なデータをセンシングして参加者の状態を推定する．グループディスカッション中の参加者の心拍，発言録から得られた感情極性，顔のランドマーク座標，他者からの感情アノテーションの 4 種類の指標から，他者への感情アノテーションを推定するために Light GBM (Gradient Boosting Machine)，SVR (Support Vector Regression) の解析を行った結果，平均絶対誤差に関して 1.780 という結果を算出した SVR のほうが良いモデルであることがわかった．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"7","bibliographic_titles":[{"bibliographic_title":"研究報告知能システム（ICS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-03-03","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicVolumeNumber":"2022-ICS-206"}]},"relation_version_is_last":true,"weko_creator_id":"44499"}}