Machine learning for speaker recognition

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...

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Detalles Bibliográficos
Otros Autores: Mak, M. W., autor (autor), Chien, Jen-Tzung, autor
Formato: Libro electrónico
Idioma:Inglés
Publicado: Cambridge : Cambridge University Press 2020.
Colección:CUP ebooks.
Acceso en línea:Conectar con la versión electrónica
Ver en Universidad de Navarra:https://innopac.unav.es/record=b4540141x*spi
Descripción
Sumario: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.
Descripción Física:1 recurso electrónico (xviii, 309 páginas)
Formato:Forma de acceso: World Wide Web.
ISBN:9781108552332