601.467/667 Introduction to Human Language Technology

Fall 2020

Coordinator: Philipp Koehn (phi@jhu.edu)
TAs: Desh Raj (draj2@jhu.edu)
Class: Tuesday and Thursday 9:00-10:15am, Online (MS Teams)
Office hours: Coordinator: TBD
Office hours: Desh Raj: TBD
Gradescope ☆ Piazza

Assignments

  1. N-gram language modeling, CYK parsing: Due on September 25 (Friday)
  2. Neural networks, RNN language models: TBD
  3. Phoneme classification: TBD
  4. End-to-end speech recognition: TBD
  5. Sequence classification (transfer learning): TBD

Exam

There will be a mid-term and final exam. The exam is open book. The final exam time TBD.
Example questions for the final exam.

Lectures

Date Topic Instructor
Tu Sep 1IntroductionKoehn
Text
Th Sep 3Words and Language ModelsYarowsky
Tu Sep 8MorphologyYarowsky
Th Sep 10SyntaxPost
Tu Sep 15SemanticsPost
Th Sep 17Deep learning IWatanabe
Tu Sep 22Deep learning IIWatanabe
Th Sep 24Distributional SemanticsKoehn
Tu Sep 29Information RetrievalDuh
Th Oct 1Information ExtractionKoehn
Tu Oct 6Machine TranslationDuh
Th Oct 8First Midterm Exam-
Speech
Tu Oct 13Auditory systemElhilali
Th Oct 15Speech basicsHermansky
Tu Oct 20Classic speech recognition1 (additional slides)Khudanpur
Th Oct 22Hands on: KaldiKhudanpur
Tu Oct 27Speaker recognitionDehak
Th Oct 29Signal processing (Chapter 6)Khudanpur
Tu Nov 3End-to-end neural speech recognitionWatanabe
Th Nov 5Hands on: Deep learningWatanabe
Tu Nov 10Second Midterm Exam-
Applications
Th Nov 12NLP for Digital HumanitiesLippincott
Tu Nov 17Question AnsweringDuh
Th Nov 19Dialog SystemsSedoc
Tu Dec 1Clinical NLPDredze
Th Dec 3Ethical ProblemsMoro-Velazquez
Tu Dec 9Analyzing and Interpreting Neural Networks for NLPLinzen
Th Dec 11Review sessionKoehn
1These slides present an incomplete picture of what will be discussed in class. Attentive listening is recommended for gaining maximal benefit.