Computational Linguistics detailed syllabus for Information Technology (IT) for 2019 regulation curriculum has been taken from the Anna Universities official website and presented for the IT students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.
For Information Technology 8th Sem scheme and its subjects, do visit IT 8th Sem 2019 regulation scheme. For Professional Elective-VII scheme and its subjects refer to IT Professional Elective-VII syllabus scheme. The detailed syllabus of computational linguistics is as follows.
Course Objective:
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Unit I
Foundations
Formal Language Theory – Language Classes and Linguistic Formalisms – Regular Languages – Context-Free Languages – The Chomsky Hierarchy – Mildly Context-Sensitive Languages.
Suggested Activities:
- Assignments on problem solving using regular expressions.
- Assignments on solving exercises using context free grammars.
- In-class discussion on collected papers related with natural language applications of finite state technology.
Suggested Evaluation Methods:
- Assignment problems on regular expressions and context free grammars.
- Quizzes on different topics of the unit.
Unit II
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Unit III
Statistical Language Modeling
Introduction – Measures of Language Model Quality – Structured Language Model -Probabilistic Model – Theory of Parsing – Context-Free Grammars and Recognition -Context-Free Parsing – Probabilistic Parsing – Lexicalized Context-Free Grammars -Dependency Grammars – Tree Adjoining Grammars – Automatic Translation.
Suggested Activities:
- Solving simple problems using metrics for evaluating language models.
- Demonstrating real world applications involving language constraints using context free grammars.
Suggested Evaluation Methods:
- Case study on writing simple parsers in groups for regional languages.
- Case study on using real time parsers for various web applications.
- Assignments on CFGs.
Unit IV
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Unit V
Domains of Application
Speech Recognition – Statistical Parsing – Segmentation and Morphology – Computational Semantics – Information Extraction – Natural Language Generation – Question Answering.
Suggested Activities:
- Case Studies on applications involving language models.
- Demonstration of simple application specific modules using tools.
Suggested Evaluation Methods:
- Quizzes on different topics of the unit.
Course Outcome:
For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier..
Text Books:
- Ruslan Mitkov, “The Oxford Handbook of Computational Linguistics”, Oxford University Press, 2003.
References:
- Rodolfo Delmonte, “Computational Linguistics, Text Processing: Logical Form, Semantic Interpretation, Discourse Relations and Question Answering”, Nova Science Publishers, 2007.
- Alfio Gliozzo, Cailo Strapparava, “Semantic Domain in Computational Linguistics”, Springer, 2009.
- James H. Martin and Daniel Jurafsky, “Speech and language processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition”, Second Edition, Pearson Education, 2014.
For detailed syllabus of all the other subjects of Information Technology 8th Sem, visit IT 8th Sem subject syllabuses for 2019 regulation.
For all Information Technology results, visit Anna University IT all semester results direct link.