bayesian speech language processing von watanabe shinji (8 Ergebnisse)

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Hardcover. Zustand: Brand New. 1st edition. 445 pages. 9.75x7.00x1.00 inches. In Stock.

Hardcover. Zustand: new. Hardcover. 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. With this comprehensive guide readers will learn how they can apply Bayesian machine learning techniques systematically to solve speech and language processing problems. Including detailed practical explanations along with examples and case studies, this is an invaluable resource for students, researchers, and industry practitioners working in speech and language processing. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Hardcover. Zustand: Like New. Like New. book.

Hardcover. Zustand: new. Hardcover. 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. With this comprehensive guide readers will learn how they can apply Bayesian machine learning techniques systematically to solve speech and language processing problems. Including detailed practical explanations along with examples and case studies, this is an invaluable resource for students, researchers, and industry practitioners working in speech and language processing. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardcover. Zustand: new. Hardcover. 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. With this comprehensive guide readers will learn how they can apply Bayesian machine learning techniques systematically to solve speech and language processing problems. Including detailed practical explanations along with examples and case studies, this is an invaluable resource for students, researchers, and industry practitioners working in speech and language processing. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.