Bandwidth Extension of Speech Signals / Edition 1

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Bandwidth Extension of Speech Signals provides discussion on different approaches for efficient and robust bandwidth extension of speech signals while acknowledging the influence of noise corrupted real-world signals. The book describes the theory and methods for quality enhancement of clean speech signals and distorted speech signals, such as those that have undergone a band limitation, for instance, in a telephone network. Problems and the respective solutions are discussed in regards to different approaches. The different approaches are evaluated and robustness issues for a real-time implementation are covered as well. The book includes topics related to speech coding, pattern-/ speech recognition, speech enhancement, statistics and digital signal processing in general.
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Editorial Reviews

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“The authors discuss the problem of quality enhancement of speech signals bandlimited by telephone networks with and without the presence of noise. … For the interested reader the book is worth reading since it covers together with basic aspects related to speech processing clearly described new results and techniques with the special feature that they can be optionally used without changing the existing hardware.” (Liviu Goras, Zentralblatt MATH, Vol. 1172, 2009)
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Product Details

  • ISBN-13: 9780387688985
  • Publisher: Springer US
  • Publication date: 8/12/2008
  • Series: Lecture Notes in Electrical Engineering Series , #13
  • Edition description: 2008
  • Edition number: 1
  • Pages: 190
  • Product dimensions: 6.10 (w) x 9.30 (h) x 0.60 (d)

Table of Contents

1 Introduction 1
1.1 Scope of the Book 3
1.2 Nature of Speech Signals 4
1.3 Band Limited Speech Signals 5
1.4 Organization of the Book 7
2 Speech Generation 9
2.1 Human Speech Generation Process 9
2.2 Model for the Speech Generation Process 12
2.2.1 Excitation Signal 12
2.2.2 Vocal Tract Filter 13
2.3 Basic Approach for Bandwidth Extension 14
3 Analysis Techniques for Speech Signals 17
3.1 Linear Predictive Analysis 17
3.1.1 Autocorrelation Method 22
3.1.2 Covariance Method 23
3.2 Parametric Representations of the Spectral Envelope 24
3.2.1 Tube Model 24
3.2.2 AR-Coefficients 27
3.2.3 Cepstral Coefficients 28
3.2.4 MFCCs 31
3.2.5 Line Spectral Frequencies 33
3.3 Scalar Speech Features 35
3.3.1 Zero Crossing Rate 36
3.3.2 Gradient Index 36
3.3.3 Fundamental Frequency 36
3.3.4 Kurtosis 42
3.3.5 Spectral Centroid 42
3.3.6 Energy Based Features 44
3.4 Distance Measures 48
3.4.1 Log Spectral Deviation 48
3.4.2 RMS-Log Spectral Deviation 49
3.4.3 Cepstral Distance 49
3.4.4 Likelihood Ratio Distance 50
3.4.5 Itakura Distance 50
3.4.6 Itakura-Saito Distance 51
3.4.7 Other Spectral Distance Measures 51
4 Excitation Signal Extension 53
4.1 Estimation of the Narrowband Excitation Signal 54
4.2 Extension Using Non-Linear Characteristics 55
4.2.1 Half-Way Rectification 57
4.2.2 Full-Way Rectification 57
4.2.3 Quadratic Characteristic 60
4.2.4 Cubic Characteristic 60
4.2.5 Tanh Characteristic 60
4.2.6 Benesty Characteristic 61
4.2.7 Adaptive Quadratic Characteristic 61
4.3 Extension Using Spectral Shifting/Modulation Techniques 62
4.3.1 Fixed Spectral Shifting62
4.3.2 Adaptive Spectral Shifting 63
4.4 Extension Using Function Generators 64
4.4.1 Sine Generators 64
4.4.2 White Noise Generators 64
4.5 Power Adjustment 65
4.6 Discussion 66
5 Broadband Spectral Envelope Estimation 67
5.1 Generation and Preparation of a Training Data Set 67
5.2 Estimation of the Narrowband Spectral Envelope 72
5.3 Estimation of the Broadband Spectral Envelope Using Codebooks 77
5.3.1 Codebook Training and Operation Using AR Coefficients 78
5.3.2 Codebook Training and Operation Using Cepstral Coefficients 79
5.3.3 Codebook Training and Operation Using MFCCs 84
5.3.4 Codebook Training and Operation Using LSFs 84
5.4 Estimation of the Broadband Spectral Envelope Using Neural Networks 85
5.4.1 Training and Operation Using Cepstral Coefficients 86
5.5 Estimation of the Broadband Spectral Envelope Using Linear Mapping 89
5.5.1 Training and Operation Using Cepstral Coefficients 89
5.6 Combined Approach Using Codebook Classification and Linear Mapping 90
5.6.1 Training and Operation Using Cepstral Coefficients 92
5.7 Discussion 94
6 Quality Evaluation 97
6.1 Evaluation of the Excitation Signal Extension 97
6.1.1 Objective Quality Criteria 98
6.1.2 Subjective Quality Criteria 99
6.1.3 Rank Correlation Between Objective and Subjective Results 106
6.2 Evaluation of the Envelope Estimation 107
6.2.1 Objective Quality Criteria 109
6.2.2 Subjective Quality Criteria 112
6.3 Discussion 114
7 Summary 115 A Levinson-Durbin Recursion 119 B LBG-Algorithm 123 C Generalized Delta Rule or Standard Backpropagation 125 D Stability Check 129 E Feature Distributions 131 F Evaluation Results 143 G Abbreviations and Symbols 153 G.1 Abbreviations 153 G.2 Important Symbols 154 List of Tables 157 List of Figures 161 References 167 Index 179
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