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  1. B200 工学部/工学研究科
  2. B200a 雑誌掲載論文
  3. 学術雑誌

ADAPTIVE REGRESSION BASED FRAMEWORK FOR IN-CAR SPEECH RECOGNITION

http://hdl.handle.net/2237/9447
http://hdl.handle.net/2237/9447
f52cc5c5-61cc-4343-8510-136717163de2
名前 / ファイル ライセンス アクション
takeda_501.pdf takeda_501.pdf (650.1 kB)
Item type 学術雑誌論文 / Journal Article(1)
公開日 2008-02-22
タイトル
タイトル ADAPTIVE REGRESSION BASED FRAMEWORK FOR IN-CAR SPEECH RECOGNITION
言語 en
著者 Li, Weifeng

× Li, Weifeng

WEKO 21911

en Li, Weifeng

Search repository
Itou, Katunobu

× Itou, Katunobu

WEKO 21912

en Itou, Katunobu

Search repository
Takeda, Kazuya

× Takeda, Kazuya

WEKO 21913

en Takeda, Kazuya

Search repository
Itakura, Fumitada

× Itakura, Fumitada

WEKO 21914

en Itakura, Fumitada

Search repository
アクセス権
アクセス権 open access
アクセス権URI http://purl.org/coar/access_right/c_abf2
権利
言語 en
権利情報 Copyright © 2006 IEEE. Reprinted from (relevant publication info). This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Nagoya University’s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org.
抄録
内容記述 We address issues for improving hands-free speech recognition performance in different car environments using a single distant microphone. In our previous work, we proposed a regression based enhancement method for in-car speech recognition. In this paper, we describe recent improvements and propose a data-driven adaptive regression based speech recognition system, in which both feature enhancement and model compensation are performed. Based on isolated word recognition experiments conducted in 15 real car environments, the proposed adaptive regression approach shows an advantage in average relative word error rate (WER) reductions of 52.5% and 14.8%, compared to original noisy speech and ETSI advanced front-end, respectively.
言語 en
内容記述タイプ Abstract
出版者
言語 en
出版者 IEEE
言語
言語 eng
資源タイプ
資源タイプresource http://purl.org/coar/resource_type/c_6501
タイプ journal article
出版タイプ
出版タイプ VoR
出版タイプResource http://purl.org/coar/version/c_970fb48d4fbd8a85
DOI
関連タイプ isVersionOf
識別子タイプ DOI
関連識別子 https://doi.org/10.1109/ICASSP.2006.1660067
ISBN
関連タイプ isPartOf
識別子タイプ ISBN
関連識別子 1-4244-0469-X
ISSN
収録物識別子タイプ PISSN
収録物識別子 1520-6149
書誌情報 en : IEEE International Conference on Acoustics, Speech and Signal Processing

巻 1, p. 501-504, 発行日 2006
フォーマット
application/pdf
著者版フラグ
値 publisher
URI
識別子 http://hdl.handle.net/2237/9447
識別子タイプ HDL
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