Free Bayesian Speech And Language Processing Ebooks Online
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.
Hardcover: 445 pages
Publisher: Cambridge University Press; 1 edition (July 15, 2015)
Language: English
ISBN-10: 1107055571
ISBN-13: 978-1107055575
Product Dimensions: 6.8 x 0.9 x 9.7 inches
Shipping Weight: 2.4 pounds (View shipping rates and policies)
Average Customer Review: 4.0 out of 5 stars See all reviews (1 customer review)
Best Sellers Rank: #1,618,096 in Books (See Top 100 in Books) #127 in Books > Computers & Technology > Computer Science > AI & Machine Learning > Natural Language Processing #245 in Books > Engineering & Transportation > Engineering > Telecommunications & Sensors > Signal Processing #509 in Books > Textbooks > Computer Science > Artificial Intelligence
It is a very useful reference for speech processing
Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition Bayesian Speech and Language Processing Deep Learning: Natural Language Processing in Python with Word2Vec: Word2Vec and Word Embeddings in Python and Theano (Deep Learning and Natural Language Processing Book 1) Deep Learning: Natural Language Processing in Python with GLoVe: From Word2Vec to GLoVe in Python and Theano (Deep Learning and Natural Language Processing) Deep Learning: Natural Language Processing in Python with Recursive Neural Networks: Recursive Neural (Tensor) Networks in Theano (Deep Learning and Natural Language Processing Book 3) An Introduction to Text-to-Speech Synthesis (Text, Speech and Language Technology) Speech and Language Processing Making the Bride's Father's Speech: Know What to Say and When to Say It - Be Positive, Humorous and Sensitive - Deliver the Memorable Speech (Essentials) The Complete Book of Speech Communication: A Workbook of Ideas and Activities for Students of Speech and Theatre Windows Speech Recognition Programming: With Visual Basic and ActiveX Voice Controls (Speech Software Technical Professionals) Speech Science Primer: Physiology, Acoustics, and Perception of Speech Using Speech Recognition Software: Dragon NaturallySpeaking and Windows Speech Recognition, Second Edition Pro Microsoft Speech Server 2007: Developing Speech Enabled Applications with .NET (Expert's Voice in .NET) Clinical Measurement of Speech & Voice (Speech Science) Digital Coding of Waveforms: Principles and Applications to Speech and Video (Prentice-Hall Signal Processing Series) Voice and Speech Processing (Mcgraw Hill Series in Electrical and Computer Engineering) Theory and Applications of Digital Speech Processing Information Processing with Evolutionary Algorithms: From Industrial Applications to Academic Speculations (Advanced Information and Knowledge Processing) Natural Language Processing for Social Media (Synthesis Lectures on Human Language Technologies) Doing Bayesian Data Analysis: A Tutorial with R and BUGS
