This book offers a unified vision of speech and language processing, presenting state-of-the-art algorithms and techniques for both speech and text-based processing of natural language. This comprehensive work covers both statistical and symbolic approaches to language processing; it shows how they can be applied to important tasks such as speech recognition, spelling and grammar correction, information extraction, search engines, machine translation, and the creation of spoken-language dialog agents.
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Features

• Each chapter is built around one or more worked examples demonstrating the main idea of the chapter.
• Integration of speech and text processing—Merges speech processing and natural language processing fields.
• Covers all of the new statistical approaches, while still completely covering the earlier more structured and rule-based methods.

Contents

Introduction. I. WORDS.

Regular Expressions and Automata.

Morphology and Finite-State Transducers.

Computational Phonology and Text-to-Speech.

Probabilistic Models of Pronunciation and Spelling.

N-grams.

HMMs and Speech Recognition. II. SYNTAX.

Word Classes and Part-of-Speech Tagging.

Context-Free Grammars for English.

Parsing with Context-Free Grammars.

Features and Unification.

Lexicalized and Probabilistsic Parsing.

Language and Complexity. III. SEMANTICS.

Representing Meaning.

Semantic Analysis.

Lexical Semantics.

Word Sense Disambiguation and Information Retrieval. IV. PRAGMATICS.

Discourse.

Dialogue and Conversational Agents.

Natural Language Generation.

Machine Translation.