Skip to main content

Schedule is subject to change

Week Date Topic Readings (★=graduate level; ⓘ=recommended supplemental)
1 Jan 21 Introduction to Machine Translation
1 Jan 23 Universal Language in the 17th century
2 Jan 28 Machine Translation in the 1930s
2 Jan 30 Machine Translation in the 1940s
3 Feb 04 1948-1950 The Noisy Channel Model
3 Feb 06 1951-1952 - Academic MT Research Begins
4 Feb 11 1954-1966 The Decade of Optimism
4 Feb 13 1966 - The ALPAC Report
5 Feb 18 Tree-Based Models
5 Feb 20 Approaches to MT: The Vauquois Triangle
6 Feb 25 Interlingual Machine Translation
6 Feb 27 N-gram language models
7 Mar 03
7 Mar 05 Statistical Word-Based MT
8 Mar 10 Statistical Phrase-Based MT
8 Mar 12 Decoding
09 Mar 17 Spring Break
09 Mar 19 Spring Break
10 Mar 24 Introduction to neural networks
10 Mar 26 Neural networks as computation graphs
  • Koehn, "Computation Graphs", Ch. 6.0-6.1 of "Neural Machine Translation" (p. 103-104)
  • ★ Koehn, "Gradient Computations", Ch. 6.2 of "Neural Machine Translation" (p. 103-108)
  • ★ Koehn, "Hands-On: Deep Learning Frameworks", Ch. 6.3 of "Neural Machine Translation" (p. 108-114)
11 Mar 31 Feed-forward neural networks
  • Koehn, "Neural Language Models", Ch. 7.0-7.2 of "Neural Machine Translation" (p. 115-121)
11 Apr 02 Recurrent neural language models
  • Koehn, "Recurrent Neural Language Models", Ch. 7.4 of "Neural Machine Translation" (p. 122-124)
12 Apr 07 Neural machine translation
12 Apr 09 MT in the Big Picture
  • Koehn, "The Translation Problem", Ch. 1 of "Neural Machine Translation" (p. 23-37)
  • Koehn, "Uses of Machine Translation", Ch. 2 of "Neural Machine Translation" (p. 39-47)
13 Apr 14 MT in Evaluation
13 Apr 16 MT in Everyday Life
14 Apr 21 MT in the U.S. Government
14 Apr 23 MT in Industry
15 Apr 28 AI and the Turing Test
15 Apr 30 The Chinese Room
16 May 05 Exam Review