{"id":56619,"updated":"2025-01-22T04:54:34.263973+00:00","links":{},"created":"2025-01-18T23:19:59.905693+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00056619","sets":["1164:5159:5162:5163"]},"path":["5163"],"owner":"1","recid":"56619","title":["単語誤り最小化に基づく識別的リスコアリングによる音声認識"],"pubdate":{"attribute_name":"公開日","attribute_value":"2008-12-02"},"_buckets":{"deposit":"8852dd0e-a124-48c9-86e1-31e3c1e4a57c"},"_deposit":{"id":"56619","pid":{"type":"depid","value":"56619","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"単語誤り最小化に基づく識別的リスコアリングによる音声認識","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"単語誤り最小化に基づく識別的リスコアリングによる音声認識"},{"subitem_title":"Discriminative Rescoring Based on Minimization of Word Errors for Speech Recognition","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2008-12-02","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"ＮＨＫ放送技術研究所"},{"subitem_text_value":"ＮＨＫ放送技術研究所"},{"subitem_text_value":"ＮＨＫ放送技術研究所"},{"subitem_text_value":"ＮＨＫ放送技術研究所"},{"subitem_text_value":"ＮＨＫ放送技術研究所"},{"subitem_text_value":"ＮＨＫ放送技術研究所"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"NHK Science & Technical Research Laboratories","subitem_text_language":"en"},{"subitem_text_value":"NHK Science & Technical Research Laboratories","subitem_text_language":"en"},{"subitem_text_value":"NHK Science & Technical Research Laboratories","subitem_text_language":"en"},{"subitem_text_value":"NHK Science & Technical Research Laboratories","subitem_text_language":"en"},{"subitem_text_value":"NHK Science & Technical Research Laboratories","subitem_text_language":"en"},{"subitem_text_value":"NHK Science & Technical Research Laboratories","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/56619/files/IPSJ-SLP08074044.pdf"},"date":[{"dateType":"Available","dateValue":"2010-12-02"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SLP08074044.pdf","filesize":[{"value":"867.3 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"22"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"4ef882e6-1222-4cd1-97b7-eddf2a5c857c","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2008 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"小林, 彰夫"},{"creatorName":"奥, 貴裕"},{"creatorName":"本間真一"},{"creatorName":"佐藤庄衛"},{"creatorName":"今井, 亨"},{"creatorName":"都木徹"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Akio, Kobayashi","creatorNameLang":"en"},{"creatorName":"Takahiro, Oku","creatorNameLang":"en"},{"creatorName":"Shinichi, Homma","creatorNameLang":"en"},{"creatorName":"Shoei, Sato","creatorNameLang":"en"},{"creatorName":"Toru, Imai","creatorNameLang":"en"},{"creatorName":"Tohru, Takagi","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10442647","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_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"本報告では，ニュース音声認識における単語誤りの傾向を反映したリスコアリング手法を提案する．提案法では，リスコアリングの際，音声認識の単語仮説の誤り傾向に応じて，仮説にペナルティを与える．単語仮説のペナルティは，言語的な文脈により活性化する素性関数とその重みにより定義される．素性関数の重みを求めるため，単語誤り最小化に基づく学習法を提案し，学習データ中の単語誤りを削減するような目的関数を用いて学習を行う．さらに，ニュース音声認識をターゲットとした時期依存適応学習を導入し，話題の時間的な関連性を用いて認識率の改善を図る．ニュース音声を用いたリスコアリング実験の結果，提案法は単語誤り率 7.4％ となり， trigram によるラティスリスコアリングに比べて 6.3％ の単語誤り削減率が得られた．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"This paper describes a novel method of rescoring that reflects tendencies of errors in word hypotheses in speech recognition for transcribing broadcast news. The proposed rescoring assigns penalties to sentence hypotheses according to the recognition error tendencies in the training lattices themselves using a set of weighting factors for feature functions activated by a variety of linguistic contexts. We introduced new techniques to obtain the factors and it is based on the minimization of word errors, which explicitly reduces expected word errors. Moreover, we proposed a new time-dependent-adaptive training scheme, which features similarities among temporal correlated articles of broadcast news. The results of transcribing Japanese broadcast news achieved a word error rate (WER) of 7.4%, which was a 6.3% reduction relative to conventional trigram lattice rescoring.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"260","bibliographic_titles":[{"bibliographic_title":"情報処理学会研究報告音声言語情報処理（SLP）"}],"bibliographicPageStart":"255","bibliographicIssueDates":{"bibliographicIssueDate":"2008-12-02","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"123(2008-SLP-074)","bibliographicVolumeNumber":"2008"}]},"relation_version_is_last":true,"weko_creator_id":"1"}}