Machine Learning for Speaker Recognition

Erscheinungsjahr 2020
ISBN: 978-1-108-42812-5
Verlag: Cambridge University Press

Buch, Englisch, 336 Seiten, Format (B × H): 196 mm x 249 mm, Gewicht: 771 g

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.

Autoren/Hrsg.

Mak, Man-Wai

Chien, Jen-Tzung

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik
• Mathematik | Informatik EDV | Informatik Informatik Natürliche Sprachen & Maschinelle Übersetzung
• Mathematik | Informatik EDV | Informatik Business Application Mathematische & Statistische Software
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

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.

Über Autor(innen)

Mak, Man-Wai
Man-Wai Mak is Associate Professor of Department of Electronic and Information Engineering at The Hong Kong Polytechnic University.

Chien, Jen-Tzung
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.