一级黄色片免费播放|中国黄色视频播放片|日本三级a|可以直接考播黄片影视免费一级毛片

高級搜索

留言板

尊敬的讀者、作者、審稿人, 關(guān)于本刊的投稿、審稿、編輯和出版的任何問題, 您可以本頁添加留言。我們將盡快給您答復(fù)。謝謝您的支持!

姓名
郵箱
手機號碼
標題
留言內(nèi)容
驗證碼

非線性統(tǒng)計匹配用于子帶魯棒語音識別

孫暐 吳鎮(zhèn)揚 劉海濱

孫暐, 吳鎮(zhèn)揚, 劉海濱. 非線性統(tǒng)計匹配用于子帶魯棒語音識別[J]. 電子與信息學(xué)報, 2006, 28(3): 480-484.
引用本文: 孫暐, 吳鎮(zhèn)揚, 劉海濱. 非線性統(tǒng)計匹配用于子帶魯棒語音識別[J]. 電子與信息學(xué)報, 2006, 28(3): 480-484.
Sun Wei, Wu Zhen-yang, Liu Hai-bin. Nonlinear Statistical Matching for Subband Robust Speech Recognition[J]. Journal of Electronics & Information Technology, 2006, 28(3): 480-484.
Citation: Sun Wei, Wu Zhen-yang, Liu Hai-bin. Nonlinear Statistical Matching for Subband Robust Speech Recognition[J]. Journal of Electronics & Information Technology, 2006, 28(3): 480-484.

非線性統(tǒng)計匹配用于子帶魯棒語音識別

Nonlinear Statistical Matching for Subband Robust Speech Recognition

  • 摘要: 由于語音信號的多變性,識別系統(tǒng)的性能極易受噪聲環(huán)境的影響而導(dǎo)致性能下降。該文以聽覺試驗為基礎(chǔ),提出一種新的非線性獨立子帶隱馬爾可夫模型(HMM)最大后驗統(tǒng)計匹配算法。該算法依據(jù)人耳感知的頻選性,根據(jù)各子帶噪聲特點采用統(tǒng)計匹配、MAP估計和HMM/MLP非線性映射來補償噪聲環(huán)境的影響。實驗表明該算法明顯改善了識別系統(tǒng)在噪聲環(huán)境下的性能。
  • Cooke M, Morris A, Green P. Missing data techniques for robust speech recognition[C][J].ICASSP97, Munich, Germany.1997, vol 2:863-[2]Diakoloukas V D, Digalakis V V. Maximum-likelihood stochastic-transformation adaptation of hidden Markov models[J].IEEE Trans. on Speech and Audio Processing.1999, 7(2):177-[3]Siohan O, Chesta C, Lee C -H. Hidden Markov model adaptation using maximum a posteriori linear regression[C]. In Workshop on Robust Methods for Speech Recognition in Adverse Conditions, Tampere, Finland, 1999: 147150. .[4]Gales M, Young S. Cepstral parameter compensation for HMM recognition in noise[J]. Computer Speech and Language, 1993, 12(3):231.239.[5]Sharma S R. Multistream approach to robust speech recognition[D/D]. Oregon Graduate Institute of Science and Technology, 1999.10.[6]Tibrewala S, Hermansky H. Subband based recognition of noisy speech[C][J].ICASSP97, Munich, Germany.1997, vol 2:1255-[7]Ji M, Smith F J. A probabilistic union model for subband based robust speech recognition[C]. ICASSP'00, Istanbul, Turkey, 2000, vol 3: 1787.1790.[8]孫暐, 吳鎮(zhèn)揚, 劉海濱等. 并行子帶HMM最大后驗概率自適應(yīng)非線性類估計算法[J]. 電路與系統(tǒng), 錄用待刊.[9]Allen J B. How do humans process and recognize speech[J]. IEEE Trans. on Speech and Audio Processing, 1994, 2(4): 567577. .[10]Dempster A P, Laird N M, Rubin D B. Maximum likelihood estimation from incomplete data[J]. J Royal Statistical Society,Serials B, 1977, 39(1): 138. .[11]Ris C, Dupont S. Assessing local noise level estimation methods: application to noise robust ASR[J].Speech Communication.2001, 34(1-2):141-[12]Hirsh H G.. Estimation of noise spectrum and its application to SNR estimation and speech enhancement. Technical ReportTR-93-012, International Computer Science Institute, Berkeley,USA, 1993.[13]Mak B. A mathematical relationship between fullband and multiband mel-frequency cepstral coefficients[J]. IEEE Signal Processing Letters, 2002, 9(8): 241244.
  • 加載中
計量
  • 文章訪問數(shù):  2464
  • HTML全文瀏覽量:  93
  • PDF下載量:  753
  • 被引次數(shù): 0
出版歷程
  • 收稿日期:  2004-08-05
  • 修回日期:  2005-04-21
  • 刊出日期:  2006-03-19

目錄

    /

    返回文章
    返回