Speech and Language Processing
by Dan Jurafsky, James H. Martin
Publisher: Stanford University 2017
Number of pages: 499
This text takes an empirical approach to the subject, based on applying statistical and other machine-learning algorithms to large corporations. The authors cover areas that traditionally are taught in different courses, to describe a unified vision of speech and language processing. Emphasis is on practical applications and scientific evaluation.
Home page url
Download or read it online for free here:
by Edward Stabler - UCLA
What kind of computational device could use a system like a human language? This text explores the computational properties of devices that could compute morphological and syntactic analyses, and recognize semantic relations among sentences.
by Igor Boshakov, Alexander Gelbukh
The book focuses on the basic set of ideas and facts from the fundamental science necessary for the creation of intelligent language processing tools, without going deeply into the details of specific algorithms or toy systems.
by Doug Arnold, at al. - Blackwell Pub
This introductory book looks at all aspects of Machine Translation: covering questions of what it is like to use a modern Machine Translation system, through questions about how it is done, to questions of evaluating systems, and more.
by Steven Bird, Ewan Klein, Edward Loper - O'Reilly Media
This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies. With it, you'll learn how to write Python programs that work with large collections of unstructured text.