Bayesian Speech and Language Processing
Author | : | |
Rating | : | 4.69 (845 Votes) |
Asin | : | 1107055571 |
Format Type | : | paperback |
Number of Pages | : | 445 Pages |
Publish Date | : | 2014-06-04 |
Language | : | English |
DESCRIPTION:
The uncertainty modeling is crucial in increasing the robustness of practical systems based on statistical modeling under real environments, such as automatic speech recognition systems under noise, and question answering systems based on limited size of training data. This is the most advanced and comprehensive book for learning fundamental Bayesian approaches and practical techniques." Sadaoki Furui, Tokyo Institute of Technology . "This book provides an overview of a wide range of fundamental theories of Bayesian learning, inference, and prediction for uncertainty modeling in speech and language processing
He has published more than 100 papers in journals and conferences, and received several awards including the best paper award from IEICE in 2003.Jen-Tzung Chien is with the Department of Electrical and Computer Engineering and the Department of Computer Science at the National Chiao Tung University, Taiwan, where he is now the University Chair Professor. Shinji Watanabe received his PhD from Waseda University in 2006. . He received the Distinguished
With this comprehensive guide you will learn how to apply Bayesian machine learning techniques systematically to solve various problems in speech and language processing. Approximate Bayesian inferences based on MAP, Evidence, Asymptotic, VB, and MCMC approximations are provided as well as full derivations of calculations, useful notations, formulas, and rules. A range of statistical models is detailed, from hidden Markov models to Gaussian mixture models, n-gram models and latent topic models, along with applications including automatic speech recognition, speaker verification, and information retrieval. This is an invaluable resource for students, researchers, an
Four Stars It is a very useful reference for speech processing