Tuesday, July 10, 2012

IT9022-COMPUTATIONAL LINGUISTICS-ANNA UNIVERSITY SYLLABUS IT


IT9022-COMPUTATIONAL  LINGUISTICS-ANNA UNIVERSITY SYLLABUS IT


IT9022                          COMPUTATIONAL  LINGUISTICS                          L T P C
3  0 0 3
AIM:
The aim of this course is to understand the issues and challenges in tackling natural language and the use of statistical approaches in this challenging area.

OBJECTIVES:
·               To study the features of natural languages including Indian Languages
·               To grasp Morphology and Parts-of-Speech and its processing
·               To understand Probabilistic Models for language processing
·               To comprehend the models for Syntax analysis
·               To understand Semantics and Pragmatics of natural language

UNIT I             INTRODUCTION                                                                                        9
Issues Motivation Theory of Language -Features of Indian Languages Issues in
Font Coding Techniques sorting & searching issues.

UNIT II            MORPHOLOGY AND PARTS-OF-SPEECH                                           9
Phonology Computational Phonology - Words and Morphemes Segmentation Categorization and Lemmatisation Word Form Recognition Valency - Agreement - Regular Expressions and Automata Morphology- Morphological issues of Indian Languages Transliteration.

UNIT III           PROBABILISTIC MODELS                                                                      9
Probabilistic Models of Pronunciation and Spelling Weighted Automata N- Grams Corpus Analysis Smoothing Entropy - Parts-of-Speech Taggers Rule based models Hidden Markov Models Speech Recognition

UNIT IV           SYNTAX                                                                                                     9
Basic Concepts of Syntax Parsing Techniques General Grammar rules for Indian Languages   Context Free Grammar Parsing with Context Free Grammars Top Down  Parser   Earley  Algorithm   Features  and  Unificatio -  Lexicalised  and Probabilistic Parsing.

UNIT V            SEMANTICS AND PRAGMATICS                                                           9
Representin Meanin  Computational   Representation    Meaning   Structure  of Language   Semantic  Analysis   Lexical  Semantics   WordNet   Pragmatics  Discourse   Reference  Resolution   Text  Coherence   Dialogue  Conversational Agents.




TEXT BOOKS:


TOTAL:45 PERIODS


1.   Daniel  Jurafskey  and  James  H.  Martin  Speech  and  Language  Processing, Prentice Hall, 2000.
2.   Ronald  Hausser  Foundations   of  Computationa Linguistics Springer-Verleg,
1999.


REFERENCES:
1.   James Allen Natural Language  Understanding,  Benjamin/Cummings  Publishing
Co. 1995.
2.   StevYoung  and Gerrit Bloothooft  Corpus Based  Methods  in Language  and
Speech Processing, Kluwer Academic Publishers, 1997.


CLICK HERE FOR ALL SUBJECTS

7/10/2012 12:23:00 PM

0 comments:

Post a Comment

Related Posts Plugin for WordPress, Blogger...