NATURAL LANGUAGE PROCESSING

Introduction to NLP: Knowledge in speech and language processing – Ambiguity – Models and Algorithms Language, Thought and Understanding.

Regular Expressions and automata: Regular expressions – Finite-State automata. Morphology and Finite-State Transducers: Survey of English morphology – Finite-State Morphological parsing – Combining FST lexicon and rules – Lexicon-Free FSTs: The porter stammer – Human morphological processing

Word classes and part-of-speech tagging: English word classes, Tag sets for English, Part-of-speech tagging, Rule-based  and stochastic part-of-speech tagging, Transformation based tagging. Context-Free Grammars for English: Constituency, Rules and Trees – Sentence-level constructions, The noun phrase, Coordination, The verb phase and sub categorization, Auxiliaries, Spoken language syntax – Grammars equivalence and normal form, Finite-State and Context-Free grammars, Grammars and human processing.

Features and Unification: Feature structures, Unification of feature structures, Features structures in the grammar, implementing unification, Parsing with unification constraints – Types and Inheritance. Lexicalized and Probabilistic Parsing: Probabilistic context-free grammar, problems with PCFGs – Probabilistic lexicalized CFGs – Dependency Grammars – Human parsing.

Representing Meaning: Computational desiderata for representations, Meaning structure of language, First order predicate calculus, linguistically relevant concepts – Related representational approaches, Alternative approaches to meaning. Semantic Analysis: Syntax-Driven semantic analysis – Attachments for a fragment of English – Integrating semantic analysis into the early parser – Idioms and compositionality – Robust semantic analysis. Lexical semantics: relational among lexemes and their senses, WordNet: A database of lexical relations, The Internal structure of words, Creativity and the lexicon.

Word Sense Disambiguation and Information Retrieval: Selectional restriction-based disambiguation – Robust word sense disambiguation, Information retrieval other information retrieval tasks. Natural Language Generation: Introduction, Architecture, Surface realization, Discourse planning. Machine Translation: Language similarities and differences, The transfer metaphor, The Interlingua idea: Using meaning, Direct translation, Using statistical techniques – Usability and system development.