Prerequisite courses: none, but Regular Languages and Finite Automata, Probability, Logic and Proof, and Artificial Intelligence cover relevant material

Aims

This course aims to introduce the fundamental techniques of natural
language processing and to develop an understanding of the limits of
those techniques. It aims to introduce some current research issues,
and to evaluate some current and potential applications.

Lectures

Introduction.
Brief history of NLP research, current applications,
generic NLP system architecture,
knowledge-based versus probabilistic
approaches.

Finite-state techniques.
Inflectional
and derivational morphology, finite-state automata in NLP, finite-state
transducers.

Prediction and part-of-speech tagging.
Corpora, simple N-grams, word prediction, stochastic tagging,
evaluating system performance.

Parsing and generation. Generative grammar, context-free
grammars, parsing and generation with context-free grammars, weights
and probabilities.

Parsing with constraint-based grammars. Constraint-based grammar,
unification.

Compositional and lexical semantics.
Simple compositional semantics in constraint-based grammar.
Semantic relations, WordNet, word senses,
word sense disambiguation.

Discourse and dialogue. Anaphora
resolution, discourse relations.

be able to describe the architecture of and basic design for a
generic NLP system ``shell''

be able to discuss the current and likely future performance of
several NLP applications, such as machine translation and email response

be able to describe briefly a fundamental technique for
processing language for several subtasks, such as
morphological analysis, parsing, word sense disambiguation etc.

understand how these techniques draw on and relate to other
areas of (theoretical) computer science, such as formal language
theory, formal semantics of programming languages, or theorem
proving

Recommended reading

* Jurafsky, D. & Martin, J. (2000). Speech and language processing. Prentice Hall.

For background reading, one of:
Pinker, S. (1994). The language instinct. Penguin.
Matthews, P. (2003). Linguistics: a very short introduction. OUP.

Although the NLP lectures don't assume any exposure to linguistics,
the course will be easier to follow if students have some
understanding of basic linguistic concepts.