Speaker Authentication

1. Front Matter

   Pages i-xxv

   PDF

2. Introduction

   • Qi (Peter) Li

   Pages 1-21

3. Multivariate Statistical Analysis and One-Pass Vector Quantization

   • Qi (Peter) Li

   Pages 23-41

4. Principal Feature Networks for Pattern Recognition

   • Qi (Peter) Li

   Pages 43-60

5. Non-Stationary Pattern Recognition

   • Qi (Peter) Li

   Pages 61-73

6. Robust Endpoint Detection

   • Qi (Peter) Li

   Pages 75-91

7. Detection-Based Decoder

   • Qi (Peter) Li

   Pages 93-110

8. Auditory-Based Time Frequency Transform

   • Qi (Peter) Li

   Pages 111-134

9. Auditory-Based Feature Extraction and Robust Speaker Identification

   • Qi (Peter) Li

   Pages 135-150

10. Fixed-Phrase Speaker Verification

    • Qi (Peter) Li

    Pages 151-156

11. Robust Speaker Verification with Stochastic Matching

    • Qi (Peter) Li

    Pages 157-164

12. Randomly Prompted Speaker Verification

    • Qi (Peter) Li

    Pages 165-177

13. Objectives for Discriminative Training

    • Qi (Peter) Li

    Pages 179-190

14. Fast Discriminative Training

    • Qi (Peter) Li

    Pages 191-206

15. Verbal Information Verification

    • Qi (Peter) Li

    Pages 207-221

16. Speaker Authentication System Design

    • Qi (Peter) Li

    Pages 223-230

17. Back Matter

    Pages 231-237

    PDF

This book focuses on use of voice as a biometric measure for personal authentication. In particular, "Speaker Recognition" covers two approaches in speaker authentication: speaker verification (SV) and verbal information verification (VIV). The SV approach attempts to verify a speaker’s identity based on his/her voice characteristics while the VIV approach validates a speaker’s identity through verification of the content of his/her utterance(s). SV and VIV can be combined for new applications. This is still a new research topic with significant potential applications. The book provides with a broad overview of the recent advances in speaker authentication while giving enough attention to advanced and useful algorithms and techniques. It also provides a step by step introduction to the current state of the speaker authentication technology, from the fundamental concepts to advanced algorithms. We will also present major design methodologies and share our experience in developing real and successful speaker authentication systems. Advanced and useful topics and algorithms are selected with real design examples and evaluation results. Special attention is given to the topics related to improving overall system robustness and performances, such as robust endpoint detection, fast discriminative training theory and algorithms, detection-based decoding, sequential authentication, etc. For example, the sequential authentication was developed based on statistical sequential testing theory. By adding enough subtests, a speaker authentication system can achieve any accuracy requirement. The procedure of designing the sequential authentication will be presented. For any presented technique, we will provide experimental results to validate the usefulness. We will also highlight the important developments in academia, government, and industry, and outline a few open issues. As the methodologies developed in speaker authentication span several diverse fields, thetutorial book provides an introductory forum for a broad spectrum of researchers and developers from different areas to acquire the knowledge and skills to engage in the interdisciplinary fields of user authentication, biometrics, speech and speaker recognition, multimedia, and dynamic pattern recognition.

• Indentification
• Speaker Autentification
• Speech Recognition
• Verification
• biometrics
• detection
• homeland security

From the reviews:

“The book covers the latest research advances within the domain of speaker authentication. … Every chapter is standalone and therefore the reader can choose and fully examine only his/her theme of interest. All the theoretical findings are tested on real-world applications and results demonstrate the potential of the presented approaches; the book is thus useful both for teaching and research, as well as for industry.” (Catalin Stoean, Zentralblatt MATH, Vol. 1233, 2012)

“This book is, among other things, proof that to be great, a technical reference does not necessarily need to be huge and ‘all inclusive.’ … techniques described, especially those for pattern recognition, are general enough to be used in almost any other area where there is a need for machine classification. … This is a superb technical book, which will also be useful outside of the speech processing area. I highly recommend it for graduate studies or as a specialized reference for those in industry.” (Vladimir Botchev, ACM Computing Reviews, June, 2012)

• Li Creative Technologies (LcT), Inc., Florham Park, USA

  Qi (Peter) Li

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