Introduction to natural language processing, Regular expressions and automata, Morphology and FSTs, Phonetics, Phonology and text-to-speech, N-grams and machine learning, Word pronunciation and spelling, Automatic speech recognition, Word classes and POS tagging; CFGs for English, Basic parsing with CFGs, Parsing problems and some solutions, Probabilistic and lexicalized parsing.
Meaning representations and semantic analysis, Lexical semantics, Word sense disambiguation, Robust semantics and information retrieval, Hidden Markov and maximum entropy models.
Text coherence and discourse structure, Reference resolution, Information status, Spoken dialogue systems, Intonation in TTS systems, New approaches to story modeling for understanding, Generation and summarization, Machine translation, Summing Up: NLP applications.
Natural Language Processing