Computer Science 248/448

Statistical Speech and Language Processing

Fall 2020

Instructor: Dan Gildea (Office hours: Mon 2:00-3:00pm, Thu 2:00-3:00pm)
TA: Will Gantt (Office hours: Tu/Th 4:00-5:00pm)
Time: Tu/Th 11:05am-12:20pm

Homeworks

Recommended resources:

Syllabus

Onwe will coverwhich means that after class you will understandif before class you have read
8/27 Perceptron for Tagging NLP = ML + DP Collins 2002
9/1 Hidden Markov Models viterbi, forward JM App A
9/3 CRFs f - E[f] McCallum 2001
9/8 Neural CRFs convexity Peng 2008
9/10 Context Free Grammars highest prob string, infinite trees JM 13
9/15 latent CRF
9/17 loss-aware CRF Kakade 2002
9/22 EM for HMM JM App A
9/24 Context Free Grammars viterbi, inside-outside
9/29 Context Free Grammars viterbi, inside-outside
10/1 Parsing minimum risk decoding, max-margin Finkel 08
10/6 Parsing crf parsing, neural parsing Durrett 2015
10/8 Weighted Deduction generalized outside computation Goodman 1999
10/13 Review
10/15 Midterm
10/20 Midterm Solutions
10/22 Pytorch tensors tutorial
10/27 Search dijkstra, knuth, a*
10/29 Beam search buckets
11/3 Dependency Parsing transition systems Eisner and Satta 1999
11/5 Machine Translation Model 1 Brown 1993
11/10 Neural Machine Translation attention Sutskever 2014, Bahdanau 2014
11/12 Neural Machine Translation BPE, BLEU Vaswani 2017, Papineni 2002, Sennrich 2016
11/17 Semantics word2vec Mikolov 2013, Pennington 2014
11/19Encoder Pretraining bert and elmo Elmo, Bert
11/24 Semantics lambda calculus JM 20, Zettlemoyer 2005, Liang 2011
12/1 Something fun
12/3 Something fun
12/8 Something fun

Grading

  • Term project: 35%
  • Homeworks: 40%
  • Midterm: 25%
  • No late homework
  • Programming assignments must be in python, and must run on class account

gildea @ cs rochester edu
October 22, 2020