{"links":{},"id":56565,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00056565","sets":["1164:5159:5160:5161"]},"path":["5161"],"owner":"1","recid":"56565","title":["音声認識器の尤度を用いた残響抑圧パラメータの教師なし 最適化"],"pubdate":{"attribute_name":"公開日","attribute_value":"2009-01-30"},"_buckets":{"deposit":"4a3ca574-516b-4af5-a250-21f8d0c838e1"},"_deposit":{"id":"56565","pid":{"type":"depid","value":"56565","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"音声認識器の尤度を用いた残響抑圧パラメータの教師なし 最適化","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"音声認識器の尤度を用いた残響抑圧パラメータの教師なし 最適化"},{"subitem_title":"Unsupervised optimization of dereverberation parameters using likelihood of speech recognizer.","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2009-01-30","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"京都大学学術情報メディアセンター"},{"subitem_text_value":"京都大学学術情報メディアセンター"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"School of Informatics, Kyoto University","subitem_text_language":"en"},{"subitem_text_value":"School of Informatics, Kyoto University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"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/56565/files/IPSJ-SLP09075004.pdf","label":"IPSJ-SLP09075004"},"date":[{"dateType":"Available","dateValue":"2011-01-30"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SLP09075004.pdf","filesize":[{"value":"1.7 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":"22"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"21b70cfe-c36f-4ee1-935f-099adf5c5980","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2009 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"ゴメス, ランディ"},{"creatorName":"河原, 達也"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Randy, Gomez","creatorNameLang":"en"},{"creatorName":"Tatsuya, Kawahara","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":"残響下での音声認識は非常に困難なタスクである。従来の残響抑圧手法の大半が、音声認識器とは独立に音声波形を修復するものであった。これに対して本研究では、音声認識に用いる音響モデルの尤度が大きくなるように、残響抑圧のパラメータを最適化するアプローチを提案し 、これをスペクトルサブトラクションに基づく方法に適用する。本手法により、残響抑圧と音響モデルの学習を統合して行うことができる。さらに音声認識(デコーディング)時にも、テストデータに対して残響抑圧パラメータの最適化を行う。大語彙連続音声認識による評価実験の結果、提案手法が従来手法に比べて、認識性能を有意に改善することを確認した。","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Speech recognition under reverberant condition is a difficult task. Most dereverberation techniques used to address this problem enhance the reverberant waveform independent to that of the speech recognizer. In this paper, we expanded and improved the conventional Spectral Subtraction-based (SS) dereverberation technique. In our proposed approach, the multi-band SS parameters are optimized to improve the recognition performance. Moreover, the system is capable of adaptively fine-tuning these parameters in the acoustic modeling phase. Experimental results show that the proposed method significantly improves the recognition performance over the conventional approach. ","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"24","bibliographic_titles":[{"bibliographic_title":"情報処理学会研究報告音声言語情報処理（SLP）"}],"bibliographicPageStart":"19","bibliographicIssueDates":{"bibliographicIssueDate":"2009-01-30","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"10(2009-SLP-075)","bibliographicVolumeNumber":"2009"}]},"relation_version_is_last":true,"weko_creator_id":"1"},"created":"2025-01-18T23:19:57.421204+00:00","updated":"2025-01-21T15:29:51.230575+00:00"}