Fr. 156.00

Machine Learning for Speaker Recognition

Anglais · Livre Relié

Expédition généralement dans un délai de 1 à 3 semaines (ne peut pas être livré de suite)

Description

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

Table des matières










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.

A propos de l'auteur

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.

Résumé

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.

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