Text: Manning and Schuetze, Foundations of Statistical Natural Language Processing
Recommended: Jurafsky and Martin, Speech and Language Processing,
Handouts from Prof. Allen
| On | we will cover | which means that after class you will understand | if before class you have read |
|---|---|---|---|
| 9/1 | Introduction | empiricism | MS ch 1 |
| 9/6 | Probability Theory | independence, information theory | MS ch 2 |
| 9/8 | Linguistic Essentials | X-bar | MS ch 3 |
| 9/13 | N-grams | deleted interpolation | MS ch 6 |
| 9/15 | N-grams | Good Turing | |
| 9/20 | Hidden Markov Models | viterbi, forward-backward | MS ch 9 |
| 9/22 | Part of Speech Tagging | EM, transformation-based learning | MS ch 10 |
| 9/27 | Signal Processing for Speech | fourier, MFCC | handout |
| 9/29 | Approaches to Speech Recognition | putting it all together | handout |
| 10/4 | Large Vocabulary Speech Recognition | beam search, rescoring | Jelinek ch 4, 5 |
| 10/6 | Large Vocabulary Speech Recognition | multistack decoding, A* | Jelinek ch 4, 5 |
| 10/11 | Collocations | t-tests | MS ch 5 |
| 10/13 | Word Sense Disambiguation | bootstrapping | MS ch 7 |
| 10/18 | Language Formalisms | Swiss German | sarkar |
| 10/20 | Parsing | charts, inside-outside | MS ch 11 |
| 10/25 | Review | ||
| 10/27 | Midterm | ||
| 11/1 | Midterm Solutions | ||
| 11/3 | Real-World Parsing | lexicalization | MS ch 12 |
| 11/8 | Machine Translation | source-channel | knight |
| 11/10 | Machine Translation | model 1, 2, 3 | |
| 11/15 | Machine Translation | decoding | germann et al. |
| 11/17 | Machine Translation | syntax-based MT | yamada & knight |
| 11/22 | Machine Translation | syntax-based decoding, inversion transduction grammar | |
| 11/29 | Clustering | k-means | MS ch 14 |
| 12/1 | Information Retrieval | Latent Semantic Analysis | MS ch 15 |
| 12/6 | Text Categorization | maximum entropy | MS ch 16 |
| 12/8 | Review | come to class with questions! |