Computational Linguistics Syllabus

Course Outline

Linguistics 581







Thu Jan 18 Chapter 1 of Jurafsky and Martin (J&M) History of Computational Linguistics. Assignment 1. Some history. Textbook intro. Polish fried fish.    
Tue Jan 23 Chapter 2 J&M [Blackboard], Finite-State Automata, Regular Expressions   Textbook Ch. 2 slides Non-deterministic automata, epsilon transitions. [Also see blackboard slides]    
Thu Jan 25 Chapter 2 [Blackboard], Text normalization, edit distance, lemmatization, segmentation.        
Tue Jan 30 Reading: Sections 3.1-3.3 of Chapter 3. Introducing words and word parts. Sections 3.4-3.9 of Chapter 3. Assignment 1 due, Assignment 2 Installing Python. Textbook Ch. 3 slides Introduction to transducers    
Thu Feb 01          
Tue Feb 06 Chapter 3. XFST intro. XFST assignment (Due Feb. 20) [Compling lab (if needed): SHW 243]      
Thu Feb 08 Chapter 3. XFST intro. FSA assignment (model answer) Jupyter notebok, PDF file Minimum edit distance revisited.    
Tue Feb 13 Chapter 4: J&M. Language modeling (Ngram models). Word counting, frequency dictionaries, simple ngram models, the training corpus. The Pollard assignment and smoothing assignment are due Feb 27, Ngrams Brief probability intro Introduction to NLTK. Peter Norvig on ngrams.    
Thu Feb 15   Maly Indonesian solution, Lakota solution, English morpheme problem solution.      
Tue Feb 20          
Thu Feb 22          
Tue Feb 27 Chapter 6: J&M. [Blackboard] Naive Bayes Classification. More generative models. Demo Script for computing ngram counts. Naive Bayes lecture.    
Thu Mar 01   Naive Bayes assignment (Due Mar 8).      
Tue Mar 06   Pollard and smoothing assignment solutions, XFST: Numerals solution, XFST: Cola Machine solution.script, Solution to J&M Exc. 3.2. Chapter 6, Chapter 9: J&M. [Blackboard] Noisy channel model, Sequence models. HMMs. Intro to HMMs, Forward/Backward Algorithm on Jason Eisner's ice cream HMM.    
Thu Mar 08   Naive Bayes assignment solution.      
Tue Mar 13 Chapter 10: J&M [Blackboard] Word-class and part of speech tagging. Rule-based taggers, decoding with HMMs. Viterbi assignment (Hardcopy due Mar. 20). Lecture. Tagging slides HMM Taggers/HMM models.    
Thu Mar 15          
Tue Mar 20   Assignment: Midterm due Apr 5. Actual midterm.pdf (Attn: this is now the 2018 midterm), Viterbi assignment answer.      
Thu Mar 22          
Tue Mar 27 H'day H'day H'day H'day H'day
Thu Mar 29 H'day H'day H'day H'day H'day
Tue Apr 03 Chapter 12. J&M Context Free Grammars of English, Treebanks Grammar assignment, Due Thurs., April 13.      
Thu Apr 05   Grammar assignment.. Jurafsky/ Martin Grammar chapter lecture (see blackboard), Tree structure: Main ideas.    
Tue Apr 10 Chapter 13, 14 J&M Parsing. CKY algorithm (bottum up parsing with a chart), Earley algorithm (top down parsing with chart), probabilistic extension of CKY. Parsing assignment (CKY) (Parts A and B Due Thurs., April 20). Jurafsky Martin parsing lecture (see blackboard).   td_parser-0.1:an implementation of a recursive descent top down recognizer.
Thu Apr 12          
Tue Apr 17 Chapter 14. Top down parsing with chart, probabilistic extension of CKY. Parsing assignment (CKY) (Part C: Probabilities, Due Thurs., April 27), Prob parsing lecture, also see Jurafsky and Martin prob parsing slides (see BlackBoard), Formal properties of PCFGs (for the mathematically inclined),    
Thu Apr 19          
Tue Apr 24 Chapter 15. Vector Semantics [Jurafsky and Martin Ch. 15, 3rd Ed, Blackboard] (Optional) Word2 Vec Assignment, CKY probability assignment calculations.      
Thu Apr 26 Chapter 12-13, 15. Review        
Tue May 01          
Thu May 03   2017 Final (Due May 11, 2017, not yet available).2016 Final. Where next? Tom Mitchell's Online Machine Learning Lectures.   Last class day