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About language Modeling with N Gram
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  Language Models Instructor: Rada Mihalcea Note: some of the material in this slide set was adapted from an NLP course taught by Bonnie Dorr at Univ. of Maryland   Slide 1 Language Models  A language model an abstract representation of a (natural) language phenomenon. an approximation to real language Statistical models predictive explicative   Slide 2 Claim  A useful part of the knowledge needed to allow letter/word predictions can be captured using simple statistical techniques. Compute: probability of a sequence likelihood of letters/words co-occurring   Why would we want to do this? Rank the likelihood of sequences containing various alternative hypotheses  Assess the likelihood of a hypothesis   Slide 3 Outline ã  Applications of language models ã  Approximating natural language ã The chain rule ã Learning N-gram models ã Smoothing for language models ãDistribution of words in language: Zipf’s law and Heaps law   
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