{"links":{},"id":75437,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00075437","sets":["1164:5159:6316:6483"]},"path":["6483"],"owner":"10","recid":"75437","title":["ウエーブレットに基づくウイナーフィルタを用いた雑音及び残響に頑健な音声認識"],"pubdate":{"attribute_name":"公開日","attribute_value":"2011-07-14"},"_buckets":{"deposit":"6cfdf500-1616-44f9-993d-646303fd60ec"},"_deposit":{"id":"75437","pid":{"type":"depid","value":"75437","revision_id":0},"owners":[10],"status":"published","created_by":10},"item_title":"ウエーブレットに基づくウイナーフィルタを用いた雑音及び残響に頑健な音声認識","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ウエーブレットに基づくウイナーフィルタを用いた雑音及び残響に頑健な音声認識"},{"subitem_title":"Robust Speech Recognition in Noisy and Reverberant Environments Using Wavelet-based Wiener Filtering","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ロバスト音声認識","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2011-07-14","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":"Academic Center for Computing and Media Studies (ACCMS), Kyoto University.","subitem_text_language":"en"},{"subitem_text_value":"Academic Center for Computing and Media Studies (ACCMS), 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/75437/files/IPSJ-SLP11087014.pdf"},"date":[{"dateType":"Available","dateValue":"2013-07-14"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SLP11087014.pdf","filesize":[{"value":"376.9 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":"2aebd7be-b3c7-48a3-be1b-d8295513cea3","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2011 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":"頑健な音声認識のために、ウエーブレット領域で雑音と残響を抑圧する方法を提案する。ウエーブレット変換のパラメータは、音声・背景雑音・遅い残響成分の各々に対して最適化し、効果的なウイナーフィルタを行うためのウイナーゲインを求める。具体的には、背景雑音と遅い残響成分を抑圧するためのウイナーゲインを独立に求めた後、両者を組み合わせる。様々な雑音や残響条件に対応できるように、雑音プロファイルと残響時間の自動同定を導入している。提案手法を大語彙連続音声認識において評価し、既存の手法に比べて有効性を確認した。","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"We present a method of enhancing the speech signal corrupted by noise and late reflection in the wavelet domain for robust automatic speech recognition (ASR). The wavelet parameters for speech, background noise and late reflection are optimized to achieve a better estimate of the Wiener gain for effective filtering. Wiener gains to compensate for the effects of background noise and late reflection are independently estimated and then combined. To cope with different noise and reverberant conditions, we introduce the noise profiles and reverberation time identification. The proposed method is evaluated in a large vocabulary continuous speech recognition (LVCSR) task, and shown to outperform several conventional methods.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告音声言語情報処理（SLP）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2011-07-14","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"14","bibliographicVolumeNumber":"2011-SLP-87"}]},"relation_version_is_last":true,"weko_creator_id":"10"},"created":"2025-01-18T23:32:32.208566+00:00","updated":"2025-01-21T21:14:42.831967+00:00"}