Speech and Natural Language Processing and the Web/Topics in Artificial Intelligence Programming

Speech and Natural Language Processing and the Web/Topics in Artificial Intelligence Programming

Course contents

• Sound : Biology of Speech Processing; Place and Manner of Articulation; Word Boundary Detection; Argmax based computations; HMM and Speech Recognition
• Words and Word Forms : Morphology fundamentals; Morphological Diversity of Indian Languages; Morphology Paradigms; Finite State Machine Based Morphology; Automatic Morphology Learning; Shallow Parsing; Named Entities; Maximum Entropy Models; Random Fields
• Structures : Theories of Parsing, Parsing Algorithms; Robust and Scalable Parsing on Noisy Text as in Web documents; Hybrid of Rule Based and Probabilistic Parsing; Scope Ambiguity and Attachment Ambiguity resolution
• Meaning : Lexical Knowledge Networks, Wordnet Theory; Indian Language Wordnets and Multilingual Dictionaries; Semantic Roles; Word Sense Disambiguation; WSD and Multilinguality; Metaphors; Coreferences
• Web 2.0 Applications : Sentiment Analysis; Text Entailment; Robust and Scalable Machine Translation; Question Answering in Multilingual Setting; Cross Lingual Information Retrieval (CLIR)

Texts and References

1. Allen, James, Natural Language Understanding, Second Edition, Benjamin/Cumming, 1995.
2. Charniack, Eugene, Statistical Language Learning, MIT Press, 1993.
3. Jurafsky, Dan and Martin, James, Speech and Language Processing, Second Edition, Prentice Hall, 2008.
4. Manning, Christopher and Heinrich, Schutze, Foundations of Statistical Natural Language Processing, MIT Press, 1999.
5. Radford, Andrew et. al., Linguistics, An Introduction, Cambridge University Press, 1999.

• Journals : Computational Linguistics, Natural Language Engineering, Machine Learning, Machine Translation, Artificial Intelligence
• Conferences : Annual Meeting of the Association of Computational Linguistics (ACL), Computational Linguistics (COLING), European ACL (EACL), Empirical Methods in NLP (EMNLP), Annual Meeting of the Special Interest Group in Information Retrieval (SIGIR), Human Language Technology (HLT).

Lecture Slides

• 23/7/09 Lecture 1 : Introduction
• 27/7/09 Lecture 2 : Machine Learning and NLP
• 28/7/09 Lecture 3 : ArgMax Computation
• 30/7/09 Lecture 4 : WSD : WordNet
• 10/8/09 Lecture 5 : Wordnet; Application in Query Expansion
• 11/8/09 Lecture 6 : Wiktionary; semantic relatedness; how toread research papers
• 19/8/09 Lecture 7 : Measures of WordNet Similarity
• 19/8/09 Lecture 8 : Quiz 1
• 25/8/09 Lecture 9 : Resnick's Measure of WordNet Similarity
• 27/8/09 Lecture 10 : Parsing Algorithms
• 31/8/09 Lecture 11 : Evidence for Deeper Structure; Top Down Parsing Algorithms
• 31/8/09 Lecture 12 : Noun Structure; Top Down Parsing Algorithms- contd.
• 01/9/09 Lecture 13 : Non-noun Structure Parsing Algorithms
• 03/9/09 Lecture 14 : Probabilistic parsing; sequence labeling, PCFG [ pdf ]
• 07/9/09 Lecture 15 : Probabilistic parsing; PCFG (contd.) [ pdf ]
• 08/9/09 Lecture 16 : Probabilistic parsing; computing probability of a sentence [pdf ]
• 10/9/09 Lecture 17 : PCFG; Arguments and Adjuncts [ pdf ]
• 22/9/09 Lecture 18 : Probabilistic parsing; inside-outside probabilities [ pdf ]
• 24/9/09 Lecture 19 : Speech : Phonetics
• 24/9/09 Lecture 20 : HMM - Combined Lecture with CS 621
• 29/9/09 Lecture 21 : Morphology - Guest Lecture by Mughdha Bapat [ pdf ]
• 30/9/09 Lecture 22 : Graphical Models for Sequence Labelling in NLP. - Guest Lecture by Anup Kulkarni
• 01/10/09 Lecture 22 : Graphical Models for Sequence Labelling in NLP (contd.).- Guest Lecture by Anup Kulkarni
• 05/10/09 Lecture 23 : Phonetics (contd.).
• 06/10/09 Lecture 24 : Consonants (place and manner of articulation) and Vowels.
• 08/10/09 Lecture 25 : Vowels (contd.) and a “grand” assignment.
• 09/10/09 Lecture 26 : Forward Backward probability; Viterbi Algorithm - Combined Lecture with CS 621
• 15/10/09 Lecture 27 : Phonology.
• 20/10/09 Lecture 28a : Sentiment Analysis and Opinions on the Web. - Guest Lecture by Aaditya Joshi.
• 20/10/09 Lecture 28b : Machine Translation and MT Tools - GIZA++ and Moses. - Guest Lecture by Nirdesh Chauhan [pdf ]
• 22/10/09 Lecture 29 : Text Entailment. - Guest Lecture by Prasad Pradip Joshi
• 26/10/09 Lecture 30 : POS Tagging.
• 27/10/09 Lecture 31 : Phonology; ASR, Speech Synthesis.
• 29/10/09 Lecture 32-33 : HMM and Viterbi.
• 02/11/09 Lecture 34 : Precision, Recall, F-score, Map.
• 03/11/09 Lecture 35 : Semantic Relations; UNL; Towards Dependency Parsing.
• 05/11/09 Lecture 36 : UNL.
• 11/11/09 Lecture 37 : Semantic Role Extraction.
• 11/11/09 Lecture 38-39 : Baum Welch Algorithm; HMM training.

Lecture slides can also be found here