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Bayesian Speech and Language Processing

2015-07-15 Computers
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Release : 2015-07-15
Genre : Computers
Kind : eBook
Book Rating : 571/5 ( reviews)

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Book Synopsis Bayesian Speech and Language Processing by : Shinji Watanabe

Download or read book Bayesian Speech and Language Processing written by Shinji Watanabe. This book was released on 2015-07-15. Available in PDF, EPUB and Kindle. Book excerpt: A practical and comprehensive guide on how to apply Bayesian machine learning techniques to solve speech and language processing problems.

Speech & Language Processing

2000-09
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Release : 2000-09
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Kind : eBook
Book Rating : 724/5 ( reviews)

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Book Synopsis Speech & Language Processing by : Dan Jurafsky

Download or read book Speech & Language Processing written by Dan Jurafsky. This book was released on 2000-09. Available in PDF, EPUB and Kindle. Book excerpt:

Bayesian Speech and Language Processing

2015-07-15 Technology & Engineering
Download Bayesian Speech and Language Processing PDF Online Free

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Release : 2015-07-15
Genre : Technology & Engineering
Kind : eBook
Book Rating : 102/5 ( reviews)

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Book Synopsis Bayesian Speech and Language Processing by : Shinji Watanabe

Download or read book Bayesian Speech and Language Processing written by Shinji Watanabe. This book was released on 2015-07-15. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Bayesian Analysis in Natural Language Processing

2022-11-10 Computers
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Release : 2022-11-10
Genre : Computers
Kind : eBook
Book Rating : 614/5 ( reviews)

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Book Synopsis Bayesian Analysis in Natural Language Processing by : Shay Cohen

Download or read book Bayesian Analysis in Natural Language Processing written by Shay Cohen. This book was released on 2022-11-10. Available in PDF, EPUB and Kindle. Book excerpt: Natural language processing (NLP) went through a profound transformation in the mid-1980s when it shifted to make heavy use of corpora and data-driven techniques to analyze language. Since then, the use of statistical techniques in NLP has evolved in several ways. One such example of evolution took place in the late 1990s or early 2000s, when full-fledged Bayesian machinery was introduced to NLP. This Bayesian approach to NLP has come to accommodate for various shortcomings in the frequentist approach and to enrich it, especially in the unsupervised setting, where statistical learning is done without target prediction examples. We cover the methods and algorithms that are needed to fluently read Bayesian learning papers in NLP and to do research in the area. These methods and algorithms are partially borrowed from both machine learning and statistics and are partially developed "in-house" in NLP. We cover inference techniques such as Markov chain Monte Carlo sampling and variational inference, Bayesian estimation, and nonparametric modeling. We also cover fundamental concepts in Bayesian statistics such as prior distributions, conjugacy, and generative modeling. Finally, we cover some of the fundamental modeling techniques in NLP, such as grammar modeling and their use with Bayesian analysis.

Bayesian Analysis in Natural Language Processing

2016-06-01 Computers
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Release : 2016-06-01
Genre : Computers
Kind : eBook
Book Rating : 219/5 ( reviews)

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Book Synopsis Bayesian Analysis in Natural Language Processing by : Shay Cohen

Download or read book Bayesian Analysis in Natural Language Processing written by Shay Cohen. This book was released on 2016-06-01. Available in PDF, EPUB and Kindle. Book excerpt: Natural language processing (NLP) went through a profound transformation in the mid-1980s when it shifted to make heavy use of corpora and data-driven techniques to analyze language. Since then, the use of statistical techniques in NLP has evolved in several ways. One such example of evolution took place in the late 1990s or early 2000s, when full-fledged Bayesian machinery was introduced to NLP. This Bayesian approach to NLP has come to accommodate for various shortcomings in the frequentist approach and to enrich it, especially in the unsupervised setting, where statistical learning is done without target prediction examples. We cover the methods and algorithms that are needed to fluently read Bayesian learning papers in NLP and to do research in the area. These methods and algorithms are partially borrowed from both machine learning and statistics and are partially developed "in-house" in NLP. We cover inference techniques such as Markov chain Monte Carlo sampling and variational inference, Bayesian estimation, and nonparametric modeling. We also cover fundamental concepts in Bayesian statistics such as prior distributions, conjugacy, and generative modeling. Finally, we cover some of the fundamental modeling techniques in NLP, such as grammar modeling and their use with Bayesian analysis.

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