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 aco...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Mak, M. W. 1965- (VerfasserIn), Chien, Jen-tzung ca. 20./21. Jh (VerfasserIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Cambridge Cambridge University Press 2020
Schlagworte:	Automatic speech recognition Biometric identification Machine learning Maschinelles Lernen Sprechererkennung
Online-Zugang:	BSB01 FHN01 URL des Erstveröffentlichers
Zusammenfassung:	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
Beschreibung:	Title from publisher's bibliographic system (viewed on 29 Jun 2020)
Beschreibung:	1 Online-Ressource (xviii, 309 Seiten)
ISBN:	9781108552332
DOI:	10.1017/9781108552332