References
All readings are optional
- Recommended: Michael Collins, Notes on Statistical NLP.
- Recommended: D. Jurafsky & James H. Martin, Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition, Prentice Hall, Second Edition, 2009. (J&M)
- Recommended: Y. Goldberg, Neural Network Methods in Natural Language Processing, 2017. (G) (available online within Cornell)
- J. Eisenstein, Introduction to Natural Language Processing, MIT Press, 2019. (complete draft available online)
- C.D. Manning & H. Schuetze, Foundations of Statistical Natural Language Processing, MIT Press, 1999. (M&S)
- P. Koehn, Neural Machine Translation (book chapter draft)
- Ian Goodfellow, Yoshua Bengio, and Aaron Courville, Deep Learning, 2016.
- Hal Daumé III, A Course in Machine Learning.
- Emily Bender, Linguistic Fundamentals for Natural Language Processing: 100 Essentials from Morphology and Syntax, Morgan & Claypool, 2013.
- Emily Bender, Linguistic Fundamentals for Natural Language Processing II: 100 Essentials from Semantics and Pragmatics, Morgan & Claypool, 2019.
- Noah Smith, Linguistic Structure Prediction, Mogran & Claypool, 2011. (available online)
NLP Conferences and Journals
The main publication venues are ACL, NACCL, EMNLP, TACL, EACL, CoNLL, and CL. All papers from these publications can be found in the ACL Anthology. NLP publications often appear in ML and AI conferences, including ICML, NeurIPS, ICLR, AAAI, IJCAI. Work in the intersection of NLP and other fields often appears in the venues of these fields, such as Computer Vision (CVPR, ICCV, ECCV, etc.) and Robotics (CoRL, RSS, ICRA, HRI, etc.). A calendar of NLP events is available here, and ACL sponsored events are listed here.