Overview
This book reflects decades of important research on the mathematical foundations of speech recognition. It focuses on underlying statistical techniques such as hidden Markov models, decision trees, the expectation-maximization algorithm, information theoretic goodness criteria, maximum entropy probability estimation, parameter and data clustering, and smoothing of probability distributions. The author's goal is to present these principles clearly in the simplest setting, to show the advantages of self-organization from real data, and to enable the reader to apply the techniques.
Full Product Details
Author: Frederick Jelinek (Ctr Lang/Speech Proc)
Publisher: MIT Press Ltd
Imprint: MIT Press
Dimensions:
Width: 15.70cm
, Height: 2.50cm
, Length: 22.90cm
Weight: 0.590kg
ISBN: 9780262100663
ISBN 10: 0262100665
Pages: 305
Publication Date: 15 January 1998
Recommended Age: From 18 years
Audience:
College/higher education
,
Professional and scholarly
,
Undergraduate
,
Postgraduate, Research & Scholarly
Format: Hardback
Publisher's Status: Out of Print
Availability: Out of stock
Reviews
For the first time, researchers in this field will have a book that will serve as the bible' for many aspects of language and speech processing. Frankly, I can't imagine a person working in this field not wanting to have a personal copy. --Victor Zue, MIT Laboratory for Computer Science
Author Information
Frederick Jelinek is Julian Sinclair Smith Professor in the Department of Electrical and Computer Engineering at Johns Hopkins University, where he is also Director for the Center for Language and Speech Processing.