Dr. Radhika Mamidi

Instructor's name: Dr. Radhika Mamidi

Instructor's email id: radhika270@gmail.com

Introduction to Computational Linguistics

ENG 270

I. Course Description: This course aims to introduce the students from various disciplines to the field of Computational Linguistics. Computational Linguistics is an interdisciplinary field which focuses on the use of computers to process or produce human language (also known as 'natural language', to distinguish it from computer languages). To this field, linguistics contributes an understanding of the special properties of language data, and provides theories and descriptions of language structure and use. Computer Science contributes theories and techniques for designing and implementing computer systems. In this course apart from the theory, the students will be made to get familiar with the already available language processing tools like POS taggers, Morph Analyzers and systems like Machine Translation.

II. Course Objectives:

At the end of the course, the student is expected to understand how computers understand and process language as we do.

Knowledge

Have linguistic background

Cognitive Skills

Understand and be able to analyze natural languages

Interpersonal Skills & Responsibility

Participate in classroom discussions

Numerical & Communication Skills

Use basic information & computer technology in language understanding

III. Course Content

Topics	No. of Weeks	Contact Hours
1. Introduction – Goal of CL, CL and its relation with other disciplines, History, Levels of language processing, some CL applications and tools	3	6
2. Part of Speech tagging – rule based and statistical approaches, word and tag frequencies, n-gram appraoch, the usefulness of automatic POS taggers, CLAWS tagger 3. Corpus processing – types of corpora, use of corpus in dictionary-making, translation, language teaching and NLP	1 1	2 2
4. Morphological Analysis – Paradigm based approach in building Morph Analysers: basic concepts in morphology, lexeme, wordforms, paradigm class, paradigm table, add-delete rules	2	4
5. Syntactic Analysis - phrase structure rules, syntactic parsing using ATNs	2	4
6. Semantic Processing – features, primitives, case frames	2	4
7. Application: Machine translation system	2	4

IV. Course Components

Component	Contact Hours	Contact Hours within semester for 13 teaching weeks
Lecture	2	26

V. Teaching Strategies

Domain	Strategy
Knowledge	Lectures
Cognitive Skills	Quiz
Interpersonal Skills & Responsibility	Individual assignments
Numerical & Communication Skills	Group discussions

VI. Course Requirements

- Regular attendance

- Assignments, quizzes

- Group discussions and presentations

- Midterm and Final examination

VII. Office Hours

Sunday: 12pm – 1pm

Wednesday: 12pm – 1pm

VIII. Student Assessment

A. Assessment Task

Domain	Assessment Task
Knowledge	Midterm and Final exam
Cognitive Skills	Quizzes
Interpersonal Skills & Responsibility	Individual assignment/ exercises
Numerical & Communication Skills	Group discussions/classroom participation

B. Schedule of Assessment

Assessment	Assessment Task	Week Due	Proportion of Final Assessment
1	Assignments/exercises/quizzes / attendance	Week	30%
2	Midterm	Week	30%
3	Final	Week	40%

v No make-up/late exams will be held at any condition. All students must write the exam on the scheduled date.

v If a student arrives 10 minutes late to the class, she will be marked absent for the hour.

IX. Learning Resources

A. References

	Title	Author	Publisher
Essential reference	Lecture Handouts	Instructor
Recommended book	Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition	Daniel Jurafsky & James H. Martin	Pearson Education Inc.
Recommended book	Computational Linguistics: Models, Resources, Applications	Igor Bolshakov, Alexander Gelbukh