Steven L. Gay, Jacob Benesty's Acoustic Signal Processing for Telecommunication PDF

By Steven L. Gay, Jacob Benesty

ISBN-10: 1441986448

ISBN-13: 9781441986443

ISBN-10: 1461346568

ISBN-13: 9781461346562

158 2. Wiener Filtering 159 three. Speech Enhancement by means of Short-Time Spectral amendment three. 1 Short-Time Fourier research and Synthesis 159 one hundred sixty three. 2 Short-Time Wiener filter out 161 three. three energy Subtraction three. four value Subtraction 162 three. five Parametric Wiener Filtering 163 164 three. 6 assessment and dialogue Averaging innovations for Envelope Estimation 169 four. 169 four. 1 relocating ordinary a hundred and seventy four. 2 Single-Pole Recursion one hundred seventy four. three Two-Sided Single-Pole Recursion four. four Nonlinear information Processing 171 five. instance Implementation 172 five. 1 Subband clear out financial institution structure 172 173 five. 2 A-Posteriori-SNR Voice task Detector five. three instance a hundred seventy five 6. end a hundred seventy five half IV Microphone Arrays 10 Superdirectional Microphone Arrays 181 Gary W. Elko 1. creation 181 2. Differential Microphone Arrays 182 three. Array Directional achieve 192 four. optimum Arrays for Spherically Isotropic Fields 193 four. 1 greatest achieve for Omnidirectional Microphones 193 four. 2 greatest Directivity Index for Differential Microphones 195 four. three Maximimum Front-to-Back Ratio 197 four. four minimal top Directional reaction two hundred four. five Beamwidth 201 five. layout Examples 201 five. 1 First-Order Designs 202 five. 2 Second-Order Designs 207 five. three Third-Order Designs 216 five. four Higher-Order designs 221 6. optimum Arrays for Cylindrically Isotropic Fields 222 6. 1 greatest achieve for Omnidirectional Microphones 222 6. 2 optimum Weights for max Directional achieve 224 6. three resolution for optimum Weights for max Front-to-Back Ratio for Cylindrical Noise 225 7. Sensitivity to Microphone Mismatch and Noise 230 8.

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Widrow and S. D. Stearns, Adaptive Signal Processing. , 1985. [14] S. J. Orfanidis, Optimum Signal Processing: An Introduction. , 1988. [15] S. Haykin, Adaptive Filter Theory. , 1996. [16] J. S. Lim and A. V. Oppenheim, "Enhancement and bandwidth compression of noisy speech," Proc. of the IEEE, vol. 67, pp. 1586-1604, Dec. 1979. [17] R. Martin, "Spectral subtraction based on minimum statistics," in Proc. EUSIPCO, 1994, pp. 1182-1185. I MONO· CHANNEL ACOUSTIC ECHO CANCELLATION Chapter 2 THE FAST AFFINE PROJECTION ALGORITHM Steven L.

31) slightly, el,n-l = [I - JLX~_IXn-1 [X~_IXn-1 + aIr l ] en-I. 40) where V n-l is an N by N unitary matrix and An-l is a N by N diagonal matrix with its i th diagonal element being the i th eigenvalue of X~_l Xn-l, Ai,n-l. // ~ . . . o. 44) Assume that 8 is chosen to be approximately equal to the power of Yn' Then, for those modes where, Ai,n-l « 8, n-l is mainly dominated by the background noise and little can be learned fro~ it about h ep . So, suppressing these modes by multiplying them by 1 - JL will attenuate somewhat the background noise's effect on the overall echo path estimate.

2. Sn is the desired or the system output signal. It is the echo plus any additional signal added in the echo path such as near-end speech or background noise. 3. h n = [ho,n, hl,n, ... ,hL-I,nF where hi,n is the ith adaptive tap weight or coefficient at time n . 4. en is the a priori error (or simply, the "error") or the residual echo. 7) where hn is chosen so as to decrease the value of J (h). 11) h=hn-l where the constant of proportionality, fL is called the stepsize. 1) in the last step. 12) is simply ignored.

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Acoustic Signal Processing for Telecommunication by Steven L. Gay, Jacob Benesty


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