{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00178818","sets":["1164:5159:9063:9162"]},"path":["9162"],"owner":"11","recid":"178818","title":["応答義務推定の補助としての繰り返し発話検出"],"pubdate":{"attribute_name":"公開日","attribute_value":"2017-05-08"},"_buckets":{"deposit":"42fb4c2e-dab5-4723-b691-e7ced7a796b0"},"_deposit":{"id":"178818","pid":{"type":"depid","value":"178818","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"応答義務推定の補助としての繰り返し発話検出","author_link":["384057","384050","384055","384053","384052","384051","384049","384054","384048","384056"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"応答義務推定の補助としての繰り返し発話検出"},{"subitem_title":"Repetition Detection as a Failure Recovery of Response Obligation 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Uniersity","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/178818/files/IPSJ-SLP17116002.pdf","label":"IPSJ-SLP17116002.pdf"},"date":[{"dateType":"Available","dateValue":"2019-05-08"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SLP17116002.pdf","filesize":[{"value":"1.1 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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":"2188-8663","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"応答義務推定とは，発話区間に含まれる音響情報とユーザの振る舞いを特徴量とし，対話ロボットに応答すべきユーザ発話を推定する能力を与える技術である．しかし，ユーザの振る舞いは人それぞれであり，未学習の振る舞いに対して応答義務推定が失敗することは避けられない．この時発生するエラーの 1 つがユーザ発話の無視である．一方で，発話を無視されたユーザは同じ発話の繰り返しでエラーから回復を図ると期待される．そうであれば，高精度に繰り返し発話を検出することで，応答義務推定の失敗をカバーし，インタラクションの質を向上できると考えられる．本研究では応答義務推定の補助を目的とし，機械学習を用いた繰り返し発話検出を試みる．合成音声と人間音声を用いた評価実験により，提案特徴量の有効性を確認できた．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"7","bibliographic_titles":[{"bibliographic_title":"研究報告音声言語情報処理（SLP）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2017-05-08","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicVolumeNumber":"2017-SLP-116"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"id":178818,"updated":"2025-01-20T04:58:33.789464+00:00","links":{},"created":"2025-01-19T00:48:06.947149+00:00"}