Machine Learning for Speaker Recognition
Cambridge University Press, 11/19/2020
EAN 9781108428125, ISBN10: 1108428126
Hardcover, 334 pages, 24.8 x 17.1 x 1.9 cm
Language: English
Originally published in English
This book will help readers understand fundamental and advanced statistical models and deep learning models for robust speaker recognition and domain adaptation. This useful toolkit enables readers to apply machine learning techniques to address practical issues, such as robustness under adverse acoustic environments and domain mismatch, when deploying speaker recognition systems. Presenting state-of-the-art machine learning techniques for speaker recognition and featuring a range of probabilistic models, learning algorithms, case studies, and new trends and directions for speaker recognition based on modern machine learning and deep learning, this is the perfect resource for graduates, researchers, practitioners and engineers in electrical engineering, computer science and applied mathematics.
Part I. Fundamental Theories
1. Introduction
2. Learning algorithms
3. Machine learning models
Part II. Advanced Studies
4. Deep learning models
5. Robust speaker verification
6. Domain adaptation
7. Dimension reduction and data augmentation
8. Future direction
Index.