Bayesian Speech and Language Processing Hardback
by Shinji Watanabe, Jen-Tzung (National Chiao Tung University, Taiwan) Chien
Hardback
Description
With this comprehensive guide you will learn how to apply Bayesian machine learning techniques systematically to solve various problems in speech and language processing.
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.
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.
The authors address the difficulties of straightforward applications and provide detailed examples and case studies to demonstrate how you can successfully use practical Bayesian inference methods to improve the performance of information systems.
This is an invaluable resource for students, researchers, and industry practitioners working in machine learning, signal processing, and speech and language processing.
Information
-
Available to Order - This title is available to order, with delivery expected within 2 weeks
- Format:Hardback
- Pages:445 pages, 13 Tables, black and white; 14 Halftones, unspecified; 45 Line drawings, unspecified
- Publisher:Cambridge University Press
- Publication Date:15/07/2015
- Category:
- ISBN:9781107055575
Other Formats
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- PDF from £75.64
Information
-
Available to Order - This title is available to order, with delivery expected within 2 weeks
- Format:Hardback
- Pages:445 pages, 13 Tables, black and white; 14 Halftones, unspecified; 45 Line drawings, unspecified
- Publisher:Cambridge University Press
- Publication Date:15/07/2015
- Category:
- ISBN:9781107055575
