{"created":"2025-01-19T01:12:03.627076+00:00","updated":"2025-01-19T18:00:09.360468+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00210859","sets":["6164:6165:6640:10580"]},"path":["10580"],"owner":"44499","recid":"210859","title":["自然な食事環境下で収集した食事音声データによる 食事詳細行動分類手法の提案"],"pubdate":{"attribute_name":"公開日","attribute_value":"2020-06-17"},"_buckets":{"deposit":"b69c5a95-5a8a-4d5a-8b17-004c831b5e2b"},"_deposit":{"id":"210859","pid":{"type":"depid","value":"210859","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"自然な食事環境下で収集した食事音声データによる 食事詳細行動分類手法の提案","author_link":["534659","534661","534662","534660"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"自然な食事環境下で収集した食事音声データによる 食事詳細行動分類手法の提案"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"行動認識","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2020-06-17","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"青山学院大学"},{"subitem_text_value":"青山学院大学"},{"subitem_text_value":"青山学院大学"},{"subitem_text_value":"青山学院大学"}]},"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/210859/files/IPSJ-DICOMO2020146.pdf","label":"IPSJ-DICOMO2020146.pdf"},"date":[{"dateType":"Available","dateValue":"2022-06-17"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DICOMO2020146.pdf","filesize":[{"value":"1.2 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"36a8727b-2766-4ae4-b325-c859784528d0","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2020 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"蒲地, 遥"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"近藤, 匠海"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"横窪, 安奈"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Lopez, Guillaume"}],"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_18_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"早食いの人ほど BMI が高いことと，食事中の会話が少ないと肥満の傾向があることが分かっている．そのため，食事中の咀嚼回数と会話を増やすことが望ましい．一方，食事行動の識別は実験環境下でしか行われていない．そこで本研究では，自然な食事環境下での食事行動の定量化を目的とし，自然な食事環境下で収集した食事音声データを利用して食事詳細行動の分類を行う．骨伝導マイクロフォンを用いた食事行動分類の研究は今までにも行われているが，リサンプリングのタイミングによる学習モデルの過学習の可能性がある．また，分類する行動の種類が十分でない．この研究では，日常的な食事環境での食事音声データを収集し，分類手法を評価する．","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"1007","bibliographic_titles":[{"bibliographic_title":"マルチメディア，分散協調とモバイルシンポジウム2165論文集"}],"bibliographicPageStart":"1004","bibliographicIssueDates":{"bibliographicIssueDate":"2020-06-17","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2020"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":210859,"links":{}}