Machine Learning for Speaker Recognition

Learn fundamental and advanced machine learning techniques for robust speaker recognition and domain adaptation with this useful toolkit.

List of contents

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.

About the author

Man-Wai Mak is Associate Professor of Department of Electronic and Information Engineering at The Hong Kong Polytechnic University.Jen-Tzung Chien is a Chair Professor at the Department of Electrical and Computer Engineering, National Chiao Tung University, Taiwan. He has published extensively, including the book Bayesian Speech and Language Processing (Cambridge 2015). He is currently serving as an elected member of the IEEE Machine Learning for Signal Processing (MLSP) Technical Committee.

Summary

Understand fundamental and advanced statistical and deep learning models for robust speaker recognition and domain adaptation. Presenting state-of-the-art machine learning techniques for speaker recognition, this useful toolkit is perfect for graduates, researchers, and engineers in electrical engineering, computer science and applied mathematics.

Product details

• Authors: Jen-Tzung Chien, Jen-Tzung (National Chiao Tung University Chien, Chien Jen-Tzung, Man-Wai Mak, Man-Wai (Hong Kong Polytechnic University) Mak, Man-Wai (The Hong Kong Polytechnic University Mak, Man-Wai (The Hong Kong Polytechnic University) Mak, Mak Man-Wai
• Publisher: Cambridge University Press ELT
• Languages: English
• Product format: Hardback
• Released: 31.08.2020
• EAN: 9781108428125
• ISBN: 978-1-108-42812-5
• No. of pages: 334
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > Application software; machine learning, TECHNOLOGY & ENGINEERING / Signals & Signal Processing, Technology & Industrial Arts, Mathematical & statistical software, Applied mathematics, Natural language & machine translation, Electronics & Communications Engineering, Natural language and machine translation, Mathematical and statistical software, Electronics and communications engineering