Natural Language Processing (Level 1)
Purpose
The aim of this course is to give a research-oriented overview
of natural language processing focusing on the following two
questions:
- What are the standard methods used in the field?
- What are the current research problems?
The course is aimed both at students with limited knowledge
of the field, for whom it is compulsory within GSLT, and at
students with a more extensive background in natural language
processing, who will be expected to take more active part in
the discussion of current research. In this way, the course
is meant to contribute to the common platform for students
with different backgrounds within GSLT.
Contents
The course is divided into four study periods, each covering
a subfield of natural language processing:
- Words:
- Finite-state morphology
- Statistical language modeling (n-grams)
- Syntax:
- Part-of-speech tagging
- Syntactic parsing
- Semantics:
- Compositional semantic analysis
- Word sense disambiguation
- Pragmatics:
- Discourse processing
- Natural language generation
- Machine translation
The course requirements includes practical assignments in each study
period and a term paper for the closing seminar.
Prerequisites
The course has no special requisites over and above what is required
for admission to GSLT.