基于谱减法的语音增强算法
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资料包括： 论文(8页4449字)
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第一章 简介
第二章 算法推导
第三章 开发实现
第四章 各种方法对比讨论
第五章 结论
第六章 专用名词解释
参考文献：
J. S. Lim and A. V. Oppenheim, “Enhancement and bandwidth compression of noisy speech,” Proc. IEEE, vol. 67, pp. 1586–1604, Dec.1979.
J. S. Chang and Y. C. Tong, “A low power time-multiplexed switched capacitor speech spectrum analyzer,” IEEE J. Solid-State Circuits, vol. 28, pp. 40–49, 1993.
Y. C. Tong, R. C. Dowell, P. J. Blamey, and G. M. Clark, “Two component hearing sensations produced by two-electrode stimulation in the cochlea of a totally deaf patient,” Science, vol. 219, pp. 993–994, 1983.
Y. C. Tong, P. M. Seligman, G. M. Clark, J. F. Patrick, and J. B. Millar, “Speech processors,” U.S. Patent 4 441 202, 1984.
M. R. Weiss, E. Aschkenasy, and T. W. Parsons, “Study and development of the INTEL technique for improving speech intelligibility,” Final Rep. NSC-FR/4023, Nicolet Scientific Corp., Dec. 1974.
J. S. Lim, “Evaluation of a correlation subtraction method for enhancing speech degraded by additive white noise,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-26, pp. 471–472, Oct. 1978.
J. R. Deller, J. G. Proakis, and J. H. L. Hansen, Discrete-Time Processing of Speech Signals. New York: Maxwell Macmillian, 1993, p. 509.
D. L. Wang and J. S. Lim, “The unimportance of phase in speech enhancement,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-30, pp. 679–681, Aug. 1982.
M. Berouti, R. Schwartz, and J. Makhoul, “Enhancement of speech corrupted by acoustic noise,” in Proc. ICASSP, pp. 208–211, Apr. 1979.
S. F. Boll, “Suppression of acoustic noise in speech using spectral subtraction,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-27, pp. 113–120, Apr. 1979.
W. M. Kushner, G. Vladimir, C. Wu, V. Nguyen, and J. N. Damoulakis, “The effects of subtractive-type speech enhancement/noise reduction algorithms on parameter estimation for improved recognition and coding in high noise environments,” in Proc. ICASSP, pp. 211–214, 1989.
S. Vaseghi and R. Frayling-Cork, “Restoration of old gramophone recordings,” J. Audio Eng., vol. 40, pp. 791–801, 1992.
R. M. Crozier, B. M. G. Cheetham, C. Holt, and E. Munday, “Speech enhancement employing spectral subtraction and linear predictive analysis,” Electron. Lett., vol. 29, pp. 1094–1095, June 1993.
R. J. McAulay and M. L. Malpass, “Speech enhancement using a softdecision noise suppression filter,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-28, pp. 137–145, Apr. 1980.
[15] Y. Ephraim and D. Malah, “Speech enhancement using a minimum mean-square error short-time spectral amplitude estimator,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-32, pp. 1109–1121, Dec. 1984.
[16] , “Speech enhancement using a minimum mean-square error log-spectral amplitude estimator,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-33, pp. 443–445, Apr. 1985.
[17] O. Capp´e, “Elimination of the musical noise phenomenon with the Ephraim and Malah noise suppressor,” IEEE Trans. Speech Audio Processing, vol. 2, pp. 345–349, Apr. 1994.
[18] R. E. Crochiere, “A weighted overlap-add method of short-time Fourier analysis/synthesis,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-28, pp. 99–102, Feb. 1980.
[19] M. R. Spiegel, Schaum’s Outline of Theory and Problems of Mathematical Handbook of Formulas and Tables, Int. ed. New York: McGraw-Hill, 1990.
[20] B. Picinbono, Random Signals and Systems. Englewood Cliffs, NJ:Prentice-Hall, 1993.
[21] G. S. Kang and L. J. Fransen, “Quality improvement of LPC-processed speech by using spectral subtraction,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 37, pp. 939–942, June 1989.
[22] Sunil D. Kamath and Philipos C. Loizou,” A Muti=Band Spectral Subtraction Method For Enhancing Speech corrupted by Colored Noise ”, Department of Electrical Engineering
University of Texas at Dallas
[23]Yariv Ephramin, Fello, IEEE, and Harry L.Van Trees, Life Fellow, IEEE, “A Signal Subspace Approach for Speech Enhancement”, IEEE Transactions on Speech And Audio Processing, Vol 3. No.4.July,1995
[24]中大图书馆,《语音信号处理》
作者点评：
写作心得、体会、及文章所获其他评价
资料包括： 论文(8页4449字)
说明：
论文摘要
谱减法是消除噪音的经典算法，它有多个版本的改进方法，原始谱减法和它的各种改进方法可以归纳为一个通用谱减法参数公式，本文从这个公式出发，运用最小平均方差(MMSE)的方法进行参数优化，得到约束的短时语音谱估计器和非约束的短时语音谱估计器，它们在保持谱减法计算简单的优点的同时更好的消除了噪音。这两种估计器不同于以往的估计器。以往的都是非统计性的估计器，是靠经验来调整参数的。而本文提出的估计器是统计性估计器，是通过统计来调整估计器的参数，使之达到更好的效果。在此基础上，本文又进一步提出两种修改办法：变换带宽(Change Band-Width)方法和信噪比权值法(SNR Waiting)，研究普减法通用公式的优化。以往的消除噪音的算法都是在某个单独的确定的频带划分算法上进行的，算法割裂了相邻频带之间可能存在的联系，变换带宽方法(CBW)可以克服这个问题。信噪比权值法(SNRW)用于谱减法完成后的信号提升，尽可能的使得强信号更强，弱信号更弱，从而使语音信号得到进一步巩固。本文提出的算法最后在白色高斯噪音和粉红噪音(Pink)下测试得到满意的效果，被背景噪音污染得一片模糊的频谱图，经过消除噪音后，频谱图与未加噪音前几乎完全一样。
关键词：语音信号处理,语音增强,噪音消除
第一章 简介
噪音消除在实际生活中有很多应用，例如：话音通讯、语音识别、耳疾者特殊语音处理等等－。把各种经典谱减法概括成一个统一的参数公式，目的在于从中找出一种方便有效的单通道的自适应的谱减法。有关多通道谱减法(例如[22])以及其他消除噪音方法(例如向量子空间法[23])不是本文重点，不再提及。除了对参数的优化选择，本文还提出另外两种非参数选择上的优化，分别是变换带宽算法(CBW)和信噪比加权法(SNRW)，它们能对谱减法进一步优化，使得处理后的数据更接近没有噪音下的语音。
第一章 简介
第二章 算法推导
第三章 开发实现
第四章 各种方法对比讨论
第五章 结论
第六章 专用名词解释
参考文献：
J. S. Lim and A. V. Oppenheim, “Enhancement and bandwidth compression of noisy speech,” Proc. IEEE, vol. 67, pp. 1586–1604, Dec.1979.
J. S. Chang and Y. C. Tong, “A low power time-multiplexed switched capacitor speech spectrum analyzer,” IEEE J. Solid-State Circuits, vol. 28, pp. 40–49, 1993.
Y. C. Tong, R. C. Dowell, P. J. Blamey, and G. M. Clark, “Two component hearing sensations produced by two-electrode stimulation in the cochlea of a totally deaf patient,” Science, vol. 219, pp. 993–994, 1983.
Y. C. Tong, P. M. Seligman, G. M. Clark, J. F. Patrick, and J. B. Millar, “Speech processors,” U.S. Patent 4 441 202, 1984.
M. R. Weiss, E. Aschkenasy, and T. W. Parsons, “Study and development of the INTEL technique for improving speech intelligibility,” Final Rep. NSC-FR/4023, Nicolet Scientific Corp., Dec. 1974.
J. S. Lim, “Evaluation of a correlation subtraction method for enhancing speech degraded by additive white noise,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-26, pp. 471–472, Oct. 1978.
J. R. Deller, J. G. Proakis, and J. H. L. Hansen, Discrete-Time Processing of Speech Signals. New York: Maxwell Macmillian, 1993, p. 509.
D. L. Wang and J. S. Lim, “The unimportance of phase in speech enhancement,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-30, pp. 679–681, Aug. 1982.
M. Berouti, R. Schwartz, and J. Makhoul, “Enhancement of speech corrupted by acoustic noise,” in Proc. ICASSP, pp. 208–211, Apr. 1979.
S. F. Boll, “Suppression of acoustic noise in speech using spectral subtraction,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-27, pp. 113–120, Apr. 1979.
W. M. Kushner, G. Vladimir, C. Wu, V. Nguyen, and J. N. Damoulakis, “The effects of subtractive-type speech enhancement/noise reduction algorithms on parameter estimation for improved recognition and coding in high noise environments,” in Proc. ICASSP, pp. 211–214, 1989.
S. Vaseghi and R. Frayling-Cork, “Restoration of old gramophone recordings,” J. Audio Eng., vol. 40, pp. 791–801, 1992.
R. M. Crozier, B. M. G. Cheetham, C. Holt, and E. Munday, “Speech enhancement employing spectral subtraction and linear predictive analysis,” Electron. Lett., vol. 29, pp. 1094–1095, June 1993.
R. J. McAulay and M. L. Malpass, “Speech enhancement using a softdecision noise suppression filter,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-28, pp. 137–145, Apr. 1980.
[15] Y. Ephraim and D. Malah, “Speech enhancement using a minimum mean-square error short-time spectral amplitude estimator,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-32, pp. 1109–1121, Dec. 1984.
[16] , “Speech enhancement using a minimum mean-square error log-spectral amplitude estimator,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-33, pp. 443–445, Apr. 1985.
[17] O. Capp´e, “Elimination of the musical noise phenomenon with the Ephraim and Malah noise suppressor,” IEEE Trans. Speech Audio Processing, vol. 2, pp. 345–349, Apr. 1994.
[18] R. E. Crochiere, “A weighted overlap-add method of short-time Fourier analysis/synthesis,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-28, pp. 99–102, Feb. 1980.
[19] M. R. Spiegel, Schaum’s Outline of Theory and Problems of Mathematical Handbook of Formulas and Tables, Int. ed. New York: McGraw-Hill, 1990.
[20] B. Picinbono, Random Signals and Systems. Englewood Cliffs, NJ:Prentice-Hall, 1993.
[21] G. S. Kang and L. J. Fransen, “Quality improvement of LPC-processed speech by using spectral subtraction,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 37, pp. 939–942, June 1989.
[22] Sunil D. Kamath and Philipos C. Loizou,” A Muti=Band Spectral Subtraction Method For Enhancing Speech corrupted by Colored Noise ”, Department of Electrical Engineering
University of Texas at Dallas
[23]Yariv Ephramin, Fello, IEEE, and Harry L.Van Trees, Life Fellow, IEEE, “A Signal Subspace Approach for Speech Enhancement”, IEEE Transactions on Speech And Audio Processing, Vol 3. No.4.July,1995
[24]中大图书馆,《语音信号处理》
作者点评：
写作心得、体会、及文章所获其他评价