PPT-Reading: Ch. 5, Jurafsky

amp Martin Ch 9 3 rd Edition PI Disclosure This set includes adapted material from Rada Mihalcea Raymond Mooney and Dan Jurafsky Word classes and part of speech tagging Outline. stanfordedu sudhof jurafsky cgpottsstanfordedu Abstract We propose a computational framework for identifying linguistic aspects of polite ness Our starting point is a new corpus of requests annotated for politeness which we use to evaluate aspects of Reading Group Guide The Graveyard Bookby Neil Gaiman with illustrations by Dave McKean Philippe Matsas Books by Neil Gaiman A Selected BibliographyThe Graveyard BookWith illustrations by Dave McKeanTr Lecture 10: Wrap-up. CS 424P/ LINGUIST 287. Extracting Social Meaning and Sentiment. General Take-Away Messages. Most sentiment papers use really dumb features. .  . The field is young.  There’s lots of room for creativity!. Lecture 1: Sentiment Lexicons and Sentiment Classification. Computational Extraction of Social and Interactional Meaning. SSLST, Summer 2011. IP notice: many slides for today from . Chris Manning, William Cohen, Chris Potts . Lecture 8: Medical Applications:. Intoxication,. . Depression, Trauma, Alzheimers, General Medical Health. CS 424P/ LINGUIST 287. Extracting Social Meaning and Sentiment. Topic 1: Intoxication. Hollien et al 2001. Natural Language Processing. Spring . 2018. 14. . Context-Free Parsing. (Some slides . adapted . from . Jurafsky. & Martin). Parsing. Parsing with CFGs refers to the task of assigning proper trees to input strings. Lecture 5—1/27/2015. Susan W. Brown. Today. Big picture. What do you need to know?. What are finite state methods good for? . Review morphology. Review finite state methods. How this fits with morphology. Natural Language Processing. Spring 2018. 12. Part-Of-Speech Tagging. (Some slides . adapted . from . Jurafsky. & Martin, and . Raymond Mooney at UT Austin). 2. Grammatical Categories: Parts-of-Speech. CSC 594 Topics in AI – Natural Language Processing Spring 2018 6 . Language Models (Some slides adapted from Jurafsky & Martin) Word Prediction Guess the next word... So I notice three guys standing on the ??? CSC 594 Topics in AI – Natural Language Processing Spring 2018 10 . Part-Of-Speech Tagging, HMM (1) (Some slides adapted from Jurafsky & Martin, and Raymond Mooney at UT Austin) POS Tagging CSC 594 Topics in AI – Natural Language Processing Spring 2018 12. Part-Of-Speech Tagging (Some slides adapted from Jurafsky & Martin, and Raymond Mooney at UT Austin) 2 Grammatical Categories: Parts-of-Speech What Is the Feature Vector . x. ?. Typically a vector representation of a single character or word. Often reflects the . context. in which that word is found. Could just do counts, but that leads to sparse vectors. CS 4706. (*Thanks to Dan and Jim). Architectures of Modern Synthesis. Articulatory Synthesis:. Model movements of articulators and acoustics of vocal tract. Formant Synthesis:. Start with acoustics, create rules/filters to create each formant. Dan Jurafsky Lecture 1: Sentiment Lexicons and Sentiment Classification Computational Extraction of Social and Interactional Meaning SSLST, Summer 2011 IP notice: many slides for today from Chris Manning, William Cohen, Chris Potts and