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Introduction to Audio Analysis serves as a standalone introduction to audio analysis, providing theoretical background to many state-of-the-art techniques. It covers the essential theory necessary to develop audio engineering applications, but also uses programming techniques, notably MATLAB®, to take a more applied approach to the topic. Basic theory and reproducible experiments are combined to demonstrate theoretical concepts from a practical point of view and provide a solid foundation in the field of audio analysis.
Audio feature extraction, audio classification, audio segmentation, and music information retrieval are all addressed in detail, along with material on basic audio processing and frequency domain representations and filtering. Throughout the text, reproducible MATLAB® examples are accompanied by theoretical descriptions, illustrating how concepts and equations can be applied to the development of audio analysis systems and components. A blend of reproducible MATLAB® code and essential theory provides enable the reader to delve into the world of audio signals and develop real-world audio applications in various domains.
- Practical approach to signal processing: The first book to focus on audio analysis from a signal processing perspective, demonstrating practical implementation alongside theoretical concepts
- Bridge the gap between theory and practice: The authors demonstrate how to apply equations to real-life code examples and resources, giving you the technical skills to develop real-world applications
- Library of MATLAB code: The book is accompanied by a well-documented library of MATLAB functions and reproducible experiments
University graduates and R&D engineers needing a firm understanding of the fundamentals of audio analysis.
List of Tables
List of figures
1: Basic Concepts, Representations and Feature Extraction
1.1 The MATLAB Audio Analysis Library
1.2 Outline of Chapters
1.3 A Note on Exercises
2: Getting Familiar with Audio Signals
2.3 Mono and Stereo Audio Signals
2.4 Reading and Writing Audio Files
2.5 Reading Audio Files in Blocks
2.6 Recording Audio Data
2.7 Short-term Audio Processing
3: Signal Transforms and Filtering Essentials
3.1 The Discrete Fourier Transform
3.2 The Short-Time Fourier Transform
3.3 Aliasing in More Detail
3.4 The Discrete Cosine Transform
3.5 The Discrete-Time Wavelet Transform
3.6 Digital Filtering Essentials
3.7 Digital Filters in MATLAB
4: Audio Features
4.1 Short-Term and Mid-Term Processing
4.2 Class Definitions
4.3 Time-Domain Audio Features
4.4 Frequency-Domain Audio Features
4.5 Periodicity Estimation and Harmonic Ratio
2: Audio Content Characterization
5: Audio Classification
5.1 Classification Fundamentals
5.2 Popular Classifiers
5.3 Implementation-Related Issues
5.5 Case Studies
6: Audio Segmentation
6.1 Segmentation with Embedded Classification
6.2 Segmentation Without Classification
7: Audio Alignment and Temporal Modeling
7.1 Audio Sequence Alignment
7.2 Hidden Markov Modeling
7.3 The Viterbi Algorithm
7.4 The Baum-Welch Algorithm
7.5 HMM Training
3: Other Issues
8: Music Information Retrieval
8.1 Music Thumbnailing
8.2 Music Meter and Tempo Induction
8.3 Music Content Visualization
Appendix A: The Matlab Audio Analysis Library
1 Supplementary data
2 Supplementary data
Appendix B: Audio-Related Libraries and Software
Appendix C: Audio Datasets
- No. of pages:
- © Academic Press 2014
- 26th February 2014
- Academic Press
- Hardcover ISBN:
- eBook ISBN:
Theodoros Giannakopoulos is a Research Associate in the Institute of Informatics and Telecommunications, National Center for Scientific Research DEMOKRITOS, Greece and in the Department of Informatics & Telecommunications of the University of Athens (UOA). He received his Ph.D. degree in Audio Analysis from UOA, in 2009. His main research interests are pattern recognition, data mining, and multimedia analysis.
Research Fellow at the Institute of Informatics and Telecommunications, National Center for Scientific Research DEMOKRITOS, Greece and within the Department of Informatics & Telecommunications of the University of Athens (UOA).
Aggelos Pikrakis is a Lecturer in the Department of Informatics at the University of Piraeus. His research interests stem from the fields of pattern recognition, audio and image processing, and music information retrieval. He is also the co-author of Introduction to Pattern Recognition: A MATLAB Approach (Academic Press, 2010).
Lecturer, Department of Informatics, University of Piraeus, Greece
"...written in a sparse but graceful style, skillfully edited, and well bound. It is mostly suitable for the reader seriously interested in audio analysis who likes a mathematical programming approach to the subject."-Computing Reviews
"This new book on audio content analysis and the associated toolbox is highly recommended to audio signal processing practitioners. It can even serve as a first introduction to the more general area of pattern classification."--Computing Reviews,November 13,2014
"...excellent starting point for those who would like to learn about audio analysis techniques and develop practical skills for using MATLAB to perform audio analysis tasks." -- Noise Control Engineering Journal,May-June 2014
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