Fundamentals of Speaker Recognition
- Length: 1003 pages
- Edition: 2011
- Language: English
- Publisher: Springer
- Publication Date: 2011-12-09
- ISBN-10: 0387775919
- ISBN-13: 9780387775913
- Sales Rank: #373461 (See Top 100 Books)
An emerging technology, Speaker Recognition is becoming well-known for providing voice authentication over the telephone for helpdesks, call centres and other enterprise businesses for business process automation. “Fundamentals of Speaker Recognition” introduces Speaker Identification, Speaker Verification, Speaker (Audio Event) Classification, Speaker Detection, Speaker Tracking and more. The technical problems are rigorously defined, and a complete picture is made of the relevance of the discussed algorithms and their usage in building a comprehensive Speaker Recognition System. Designed as a textbook with examples and exercises at the end of each chapter, “Fundamentals of Speaker Recognition” is suitable for advanced-level students in computer science and engineering, concentrating on biometrics, speech recognition, pattern recognition, signal processing and, specifically, speaker recognition. It is also a valuable reference for developers of commercial technology and for speech scientists. Please click on the link under “Additional Information” to view supplemental information including the Table of Contents and Index.
Table of Contents
Part I: Basic Theory
Chapter 1 Introduction
Chapter 2 The Anatomy of Speech
Chapter 3 Signal Representation of Speech
Chapter 4 Phonetics and Phonology
Chapter 5 Signal Processing of Speech and Feature Extraction
Chapter 6 Probability Theory and Statistics
Chapter 7 Information Theory
Chapter 8 Metrics and Divergences
Chapter 9 Decision Theory
Chapter 10 Parameter Estimation
Chapter 11 Unsupervised Clustering and Learning
Chapter 12 Transformation
Chapter 13 Hidden Markov Modeling (HMM)
Chapter 14 Neural Networks
Chapter 15 Support Vector Machines
Part II: Advanced Theory
Chapter 16 Speaker Modeling
Chapter 17 Speaker Recognition
Chapter 18 Signal Enhancement and Compensation
Part III: Practice
Chapter 19 Evaluation and Representation of Results
Chapter 20 Time Lapse Effects (Case Study)
Chapter 21 Adaptation over Time (Case Study)
Chapter 22 Overall Design
Part IV: Background Material
Chapter 23 Linear Algebra
Chapter 24 Integral Transforms
Chapter 25 Nonlinear Optimization
Chapter 26 Standards