Fractional Fourier Transform Techniques for Speech Enhancement (SpringerBriefs in Speech Technology)

✍ Scribed by Prajna Kunche, N. Manikanthababu

• Publisher: Springer
• Year: 2020
• Tongue: English
• Leaves: 110
• Category: Library

✦ Synopsis

This book explains speech enhancement in the Fractional Fourier Transform (FRFT) domain and investigates the use of different FRFT algorithms in both single channel and multi-channel enhancement systems, which has proven to be an ideal time frequency analysis tool in many speech signal processing applications. The authors discuss the complexities involved in the highly non- stationary signal processing and the concepts of FRFT for speech enhancement applications. The book explains the fundamentals of FRFT as well as its implementation in speech enhancement. Theories of different FRFT methods are also discussed. The book lets readers understand the new fractional domains to prepare them to develop new algorithms. A comprehensive literature survey regarding the topic is also made available to the reader.

✦ Table of Contents

Preface
Contents
Chapter 1: Introduction
1.1 Speech Enhancement Algorithms
1.2 Time Domain Enhancement Methods
1.2.1 Comb Filtering
1.2.2 Subspace Optimal Filtering
1.2.3 Artificial Neural Network for Speech Enhancement
1.3 Transform Domain Speech Enhancement Algorithms
1.3.1 Discrete Fourier Transform
1.3.2 Wavelet Transform
1.3.3 KL Transform
1.3.4 Discrete Cosine Transform
1.4 Organization of the Book
1.5 Conclusions
References
Chapter 2: Fractional Fourier Transform
2.1 Theory of Fractional Fourier Transform
2.1.1 Properties of FrFT
2.2 Discrete Fractional Fourier Transform
2.2.1 DFrFT Based on Sampling of FrFT
2.2.2 Linear Combination Type-DFrFT
2.2.3 Group Theory Type-DFrFT
2.2.4 Impulse Train Type-DFrFT
2.2.5 Eigenvector Decomposition Type-DFrFT
2.3 Advantages of FrFT
2.4 Applications of FrFT
2.4.1 Optimal Filtering
2.4.2 Image Processing
2.4.3 Signal Analysis
2.4.4 Pattern Recognition
2.4.5 Optical Engineering
2.4.6 Cryptography
2.4.7 Communications
2.5 FrFT for Speech Enhancement Application
2.5.1 Spectral Subtraction
2.5.2 Optimal Transform for Speech Processing
2.5.3 Filtering
2.6 Conclusions
References
Chapter 3: Dual Channel Speech Enhancement Based on Fractional Fourier Transform
3.1 Basics of Adaptive Noise Cancellation
3.2 Adaptive Filters
3.2.1 LMS
3.2.2 NLMS
3.3 Application of FrFT Based ANC to Speech Enhancement
3.3.1 Continuous FrFT
3.3.2 LMS-FrFT
3.3.3 NLMS-FrFT
3.4 Simulation and Analysis
3.4.1 Parameters of Evaluation
3.4.2 Performance Analysis
3.5 Conclusions
References
Chapter 4: Fractional Cosine Transform Based Single Channel Speech Enhancement Techniques
4.1 Fundamentals of Discrete Fractional Cosine Transform
4.1.1 Properties of DFrCT
4.1.2 Advantages of DFrCT
4.1.3 Applications of DFrCT
4.2 Wiener Filter with Harmonic Regeneration Noise Reduction (W-HRNR)
4.2.1 Two Step Noise Reduction
4.2.2 Harmonic Regeneration Noise Reduction
4.3 Speech Enhancement Based on DFrCT and W-HRNR
4.4 Performance Evaluation
4.5 Conclusions
References
Chapter 5: Fractional Sine Transform Based Single Channel Speech Enhancement Technique
5.1 Concepts of DST and DFrST
5.1.1 Properties of DFrST
5.1.2 Applications of DFrST
5.2 Speech Enhancement Based on DFrST
5.3 Performance Evaluation
5.4 Results and Observations
5.5 Conclusions
References
Chapter 6: Summary and Perspectives
6.1 Summary
6.2 Future Scope
Index