CSE 40657/60657
Readings

There is no required text for this course; readings and notes will be given to you. I'll be releasing chapters of the course notes as we go. If you want to see last year's complete set of notes, please visit last year's course page.

If you like having a book for reference, an optional text is: Daniel Jurafsky and James H. Martin, Speech and Language Processing, 2nd edition, Prentice Hall, 2008. Draft chapters of the forthcoming 3rd edition are available online.

Notes

Readings for this semester will appear here as they are updated.

1. Introduction
2. Preliminaries
3. Language models: n-grams (v2)
4. Language models and finite automata (v3)
5. Language models: RNNs (v2)
6. Text input, HMMs, and FSTs (v2)
7. Speech recognition
8. Optical character recognition
9. Syntax
10. Part-of-speech tagging
11. Context-free grammars
12. Parsing
13. Statistical parsing
14. Bags of words
15. Named entity recognition and CRFs
16. Word alignment
17. Syntax-based machine translation

Jupyter notebooks

• MLE and numerical optimization

Supplementary Readings

Popular articles

• Finding a voice. Lane Greene, The Economist 2017/05/01.
• AI's Language Problem. Will Knight, MIT Technology Review, 2016/08/09.

Books

• Linguistic Fundamentals for Natural Language Processing. Emily M. Bender, 2013. [PDF via ND Library]
• Neural Network Methods in Natural Language Processing. Yoav Goldberg, 2017. [PDF via ND Library]
• Statistical Machine Translation. Philipp Koehn, 2010.
• Foundations of Statistical Natural Language Processing. Chris Manning and Hinrich Schütze, 1999.