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 ...
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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.
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Add this copy of Machine Learning for Speaker Recognition to cart. $58.80, like new condition, Sold by Prior Books rated 5.0 out of 5 stars, ships from Cheltenham, GLOUCESTERSHIRE, UNITED KINGDOM, published 2021 by Cambridge University Press.
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Seller's Description:
Like New. Size: 6x0x9; A firm, square hardback with strong joints, just showing a slight nick at the corner. Hence a non-text page is stamped 'damaged'. Despite such this book is very good condition. The contents are crisp, fresh and tight. And so it looks and feels unread and is now offered for sale at a very reasonable price.
