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El. knyga: Speech Enhancement in the STFT Domain

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This work addresses this problem in the short-time Fourier transform (STFT) domain. We divide the general problem into five basic categories depending on the number of microphones being used and whether the interframe or interband correlation is considered. The first category deals with the single-channel problem where STFT coefficients at different frames and frequency bands are assumed to be independent. In this case, the noise reduction filter in each frequency band is basically a real gain. Since a gain does not improve the signal-to-noise ratio (SNR) for any given subband and frame, the noise reduction is basically achieved by liftering the subbands and frames that are less noisy while weighing down on those that are more noisy. The second category also concerns the single-channel problem. The difference is that now the interframe correlation is taken into account and a filter is applied in each subband instead of just a gain. The advantage of using the interframe correlation is that we can improve not only the long-time fullband SNR, but the frame-wise subband SNR as well. The third and fourth classes discuss the problem of multichannel noise reduction in the STFT domain with and without interframe correlation, respectively. In the last category, we consider the interband correlation in the design of the noise reduction filters. We illustrate the basic principle for the single-channel case as an example, while this concept can be generalized to other scenarios. In all categories, we propose different optimization cost functions from which we derive the optimal filters and we also define the performance measures that help analyzing them.

Recenzijos

From the reviews:

This work addresses the problem in the short-time Fourier transform (STFT) domain. The general problem is divided into five basic categories depending on the number of microphones being used and whether the interframe or interband correlation is considered. This book is mainly a research book for people doing research in electrical and computer engineering. (Yuehua Wu, Zentralblatt MATH, Vol. 1242, 2012)

1 Introduction
1(14)
1.1 Single-Channel Speech Enhancement in the STFT Domain: A Brief Review
3(2)
1.2 Interframe Correlation
5(2)
1.3 Benefit of Using Multiple Microphones
7(2)
1.4 Interband Correlation
9(1)
1.5 Organization of the Work
10(5)
References
11(4)
2 Single-Channel Speech Enhancement with a Gain
15(14)
2.1 Signal Model
15(1)
2.2 Microphone Signal Processing with a Gain
16(1)
2.3 Performance Measures
17(6)
2.3.1 Noise Reduction
17(2)
2.3.2 Speech Distortion
19(1)
2.3.3 Mean-Square Error Criterion
20(3)
2.4 Optimal Gains
23(6)
2.4.1 Wiener
23(2)
2.4.2 Tradeoff
25(2)
2.4.3 Maximum Signal-to-Noise Ratio
27(1)
References
28(1)
3 Single-Channel Speech Enhancement with a Filter
29(22)
3.1 Microphone Signal Processing with a Filter
29(3)
3.2 Performance Measures
32(6)
3.2.1 Noise Reduction
32(3)
3.2.2 Speech Distortion
35(1)
3.2.3 MSE Criterion
36(2)
3.3 Optimal Filters
38(13)
3.3.1 Wiener
38(3)
3.3.2 Minimum Variance Distortionless Response (MVDR)
41(1)
3.3.3 Temporal Prediction
42(2)
3.3.4 Tradeoff
44(3)
3.3.5 Linearly Constrained Minimum Variance (LCMV)
47(1)
References
48(3)
4 Multichannel Speech Enhancement with Gains
51(26)
4.1 Signal Model
51(2)
4.2 Array Signal Processing with Gains
53(2)
4.3 Performance Measures
55(8)
4.3.1 Noise Reduction
55(2)
4.3.2 Speech Distortion
57(1)
4.3.3 Other Measures
58(3)
4.3.4 MSE Criterion
61(2)
4.4 Optimal Gains
63(14)
4.4.1 Maximum SNR
63(1)
4.4.2 Wiener
64(3)
4.4.3 MVDR
67(2)
4.4.4 Spatial Prediction
69(1)
4.4.5 Tradeoff
69(3)
4.4.6 LCMV
72(2)
References
74(3)
5 Multichannel Speech Enhancement with Filters
77(16)
5.1 Array Signal Processing with Filters
77(3)
5.2 Performance Measures
80(5)
5.2.1 Noise Reduction
81(1)
5.2.2 Speech Distortion
82(1)
5.2.3 MSE Criterion
83(2)
5.3 Optimal Filters
85(8)
5.3.1 Maximum SNR
85(1)
5.3.2 Wiener
86(2)
5.3.3 MVDR
88(1)
5.3.4 Spatio-Temporal Prediction
89(1)
5.3.5 Tradeoff
90(1)
5.3.6 LCMV
91(1)
References
92(1)
6 The Bifrequency Spectrum in Speech Enhancement
93(10)
6.1 Problem Formulation
93(2)
6.2 Performance Measures
95(3)
6.2.1 Noise Reduction
95(1)
6.2.2 Speech Distortion
96(1)
6.2.3 MSE Criterion
96(2)
6.3 Optimal Filtering Matrices
98(5)
6.3.1 Maximum SNR
99(1)
6.3.2 Wiener
100(1)
6.3.3 Tradeoff
101(1)
References
101(2)
7 Summary and Perspectives
103(4)
References
106(1)
Index 107