Digital Speech Processing Using Matlab deals with digital speech pattern recognition, speech production model, speech feature extraction, and speech compression. The book is written in a manner that is suitable for beginners pursuing basic research in digital speech processing. Matlab illustrations are provided for most topics to enable better understanding of concepts. This book also deals with the basic pattern recognition techniques (illustrated with speech signals using Matlab) such as PCA, LDA, ICA, SVM, HMM, GMM, BPN, and KSOM.

Autorentext

E.S. Gopi has authored four books, of which three have been published by Springer. He has also contributed 3 book chapters to books published by Springer. He has several papers in international journals and conferences to his credit. He has 15 years of teaching and research experience. He is currently Assistant Professor, Department of Electronics and Communication Engineering, National Institute of Technology, Trichy, India. He has 69 citations with h-index 4 (based on Google Scholar). His books are widely used all over the world. His research interests include pattern recognition, digital signal processing and biologically inspired algorithms. The India International Friendship Society (IIFS) has awarded him the Shiksha Rattan Puraskar Award for his meritorious services in the field of education. The award was presented by Dr. Bhishma Narain Singh, former Governor, Assam and Tamil Nadu, India. He is also awarded with the "Glory of India Gold Medal" by International Institute ofSuccess Awareness. This award was presented by Shri Syed Sibtey Razi, former Governor of Jharkhand, India. He was also awarded with "Best Citizens of India 2013" by The International Publishing House.

Klappentext

Digital Speech Processing Using Matlab deals with digital speech pattern recognition, speech production model, speech feature extraction, and speech compression. The book is written in a manner that is suitable for beginners pursuing basic research in digital speech processing. Matlab illustrations are provided for most topics to enable better understanding of concepts. This book also deals with the basic pattern recognition techniques (illustrated with speech signals using Matlab) such as PCA, LDA, ICA, SVM, HMM, GMM, BPN, and KSOM.

Inhalt
Pattern Recognition for Speech Detection.- Speech Production Model.- Feature Extraction of the Speech Signal.- Speech Compression.- Appendix A: Constrained Optimization using Lagrangian Techniques.- Appendix B: Expectation-Maximization Algorithm.- Appendix C: Diagonalization of the Matrix.- Appendix D: Condition Number.- Appendix E: Spectral Flatness.- Appendix F: Functional Blocks of the Vocal Tract and the Ear.