Lecture11-interpolation - 9/23/2011 This work is licensed...

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9/23/2011 1 CS 479, section 1: Natural Language Processing Lectures #11: Language Model Smoothing, Interpolation Thanks to Dan Klein of UC Berkeley for many of the materials used in this lecture. This work is licensed under a Creative Commons Attribution-Share Alike 3.0 Unported License . Announcements Reading Report #5 M&S 6.3 end (of ch. 6) Due: Monday Project #1, Part 1 Build an interpolated language model Questions about the requirements? ASAP: Work through the Tutorial with your pair programming partner Early: Wednesday Due: next Friday Recap: Language Models What is the purpose of a language model? What do you think are the main challenges in building n gram language models? Objectives Get comfortable with the process of factoring and smoothing a joint model of a familiar object: text! Motivate smoothing of language models Dig into Linear Interpolation as a method for smoothing Feel confident about how to use these techniques in Project #1, Part 1. Discuss how to train interpolation weights Problem Cause: Sparsity New words appear all the time: Synaptitute 132,701.03 fuzzificational New bigrams: even more often Trigrams or larger – still worse! What was the point of Zipf’s law for us?
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This note was uploaded on 10/18/2011 for the course CS 479 taught by Professor Ericringger during the Fall '11 term at BYU.

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Lecture11-interpolation - 9/23/2011 This work is licensed...

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