Special Topics in Software Engineering:

Natural Language Processing

Introductory course in the field of natural language processing and language technologies. It aims to give the students understanding of key issues related to language processing, knowledge related to the state-of-the-art in the field and to prepare them for advanced NLP courses or for specializatin in some of the perspective NLP applications (information retrieval, machine translation, speech recognition, etc.). The course is based on the book of Jurafsky and Martin "Speech and language processing".

Prerequisites of this course are: Data Structures, Models of Programming and Computing, Basic programming skills, interest in language or text.

Lecturer

Dr. Tatyana Dimitrova, University of Plovdiv, Bulgaria
tatiana@pu.acad.bg

Dates

Contents

1. Words - Regular expressions and automata, transducers, N-grams, POS tagging, Hidden Markov and Maximun Entropy models
2. Speech - phonetics, speech synthesis, automatic speech recognition
3. Syntax - formal grammars, context-free grammars. parsing, features and unification
4. Semantics and pragmatics - semantic analysis, lexical semantics, discourse
5. Applications - information retrieval, question answering, machine translation

Exam

Students will have to do a course project (the topics of this projects can be found here).

Literature

D. Jurafsky & J.H. Martin Speech and Language Processing,
http://www.cs.colorado.edu/~martin/slp.html