CS 1671: Human Language Technologies (Spring 2020)
Professor
Dr. Diane Litman (5105 Sensq)
Co-instructor
Ravneet Singh (5501 Sensq) (ras306@pitt.edu)
When & Where Tuesday and Thursdays 1:00-2:15 (via Zoom)
Office Hours Litman: Th 2:15-3:30, by appointment; Singh: M,T,Th,F 10-11:30 (via Zoom)
Description This course provides an introduction to the field of natural language processing - the creation of programs that can understand, generate, and learn languages used by humans. It will expose students to applications such as chatbots by means of computational techniques including search algorithms, dynamic programming, hidden markov models, probalistic context free grammars, and machine learning algorithms.
Prerequisites: CS 1501 (algorithms) OR consent of the instructor
Textbook: Speech and Language Processing (3rd edition online draft - free!)
Required Work Homeworks (40%): written and programming
Exams (40%): midterm and final
Group Course Project (20%): presentation and written report

Late Penalty: For assignments that may be accepted late, the penalty is 10% per day up to 5 days including Saturday, Sunday, and holidays. Assignments are due by 11:59pm.
Date/Topic (tentative)
Textbook Readings

Assignments and Other Readings

Jan 7, 9
Introduction (pdf)
Ch 1 xkcd
Humor (credits to E. Riloff for this and links below)
I. Words
Jan 9
Text Normalization (pdf)
Ch 2 (2.1-2.4) regular-expressions.info
Humor: plurals, sentence tokenization
January 10 (pdf), 14 [Singh] (pdf), 16 (pdf)
Language Modeling with N-Grams
Ch 3 (3.1-3.4) Humor
HW1: assigned 1/16, due 2/4
January 21, 23
Part-of-Speech Tagging (pdf)
Ch 8 (8.1-8.4.6) Humor
Schoolhouse Rock for Conjunctions
II. Syntax
January 24 (pdf), 28 [Singh takes over for a while](pdf),
30 (pdf)
Constituency Grammars
Ch 12 (through 12.5) Do at home: come prepared to decode "Fish sleep" using Viterbi on 1/24
Humor
January 30 (pdf), February 4 (pdf)
Constituency Parsing
Ch 13 Humor
In class Grammar
February 6 (pdf), 11 (pdf)
Statistical Constituency Parsing
Ch 14 (14.1-14.5, 14.8) Do at home: This is another example on going through the CKY algorithm that I made. The grammar is slightly simplified from the one shown in class. This is just an example you can use to review and practice the CKY algorithm.
HW2: assigned 2/11, due 2/27
III. Machine Learning
February 11 (pdf), 13 (pdf, Pictures of the Board), 18 (pdf)
Naive Bayes Classification (and Sentiment)
Ch 4 (through 4.8) Humor
Feb 13 Comment: Someone asked why 'F' was in the name of "F-measure". Going off of this paper here it was because of some name confusion with another function. Not a great explanation, but it is what it is. This paper also covers why we use harmonic mean and not normal average for F-measure.
Feb 14 Extra lesson Materials posted on Coursweb in "Course Documents" section:
Link to Courseweb
February 20 (pdf)
Logistic Regression
Ch 5 (5.1-5.2; concepts in 5.3-5.7) 9/26 NY Times: At Tech's Leading Edge, Worry about a Concentration of Power (evaluation of ML)
Midterm Review (pdf)
February 25 (pdf), 27(pdf)
Representation Learning (and Vector Semantics)
Ch 6 Word2Vec Tutorial
March 3(Board Pictures)
Neural Nets (and Language Models)
Ch 7
Ch 9
March 5 Midterm Exam (closed book) Through 2/11 class (statistical parsing). No makeups.
March 24
Dr. Litman returns and remote learning begins

Zoom links and all future class lectures available via CourseWeb (today is NoahSmithPaper.pptx)

Graded midterm review

Contextual Word Representations: A Contextual Introduction

HW3: assigned 3/24, due 4/2

From word2vec to BERT (Bidirectional Encoder Representations from Transformers)

IV. Semantics
March 26, 31; April 2
Information Extraction
Ch 18 (18.1-2)

3/31: Using New York Times Picks to Identify Constructive Comments

Project: assigned 3/31, due 4/3 (hypotheses), 4/16 (complete project)
April 2, 7, 9, 14
Word Senses and WordNet; Word Sense Disambiguation
Ch 19 humor1, humor2
April 14, 16
Semantic Role Labeling
Ch 20
April 16 (last class) Project Presentations Take Home Final Exam Assigned
Saturday April 25 8-9:50AM
(sorry, Pitt Exam Schedule)
Final Exam Due
Final Exam (closed book)
Everything since midterm (i.e., not cumulative).