PPT-N-Gram Language Models

Author : yoshiko-marsland | Published Date : 2016-06-16

CMSC 723 Computational Linguistics I Session 9 Jimmy Lin The iSchool University of Maryland Wednesday October 28 2009 NGram Language Models What LMs assign probabilities

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N-Gram Language Models: Transcript

CMSC 723 Computational Linguistics I Session 9 Jimmy Lin The iSchool University of Maryland Wednesday October 28 2009 NGram Language Models What LMs assign probabilities to sequences of tokens. Model P(hetoxf) P(thefox) 1-gram 1:83109 1:83109 2-gram 3:261011 1:18107 3-gram 1:891013 1:04106 OveralongersequenceXoflengthN,wecanalsocalculatelog2(P(X))=N,which(perShan-non)givesthecom Data-Intensive Information Processing Applications ― Session #9. Nitin Madnani. University of Maryland. Tuesday, April 6, 2010. This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States. Language Modeling. Estimating bigram probabilities. An example. Small Corpus:. <s. > I am Sam </s>. <s> Sam I am </s>. <s> I do not like green eggs and ham </s>. More examples: . Corpora and Statistical Methods. Lecture 7. In this lecture. We consider one of the basic tasks in Statistical NLP:. language models . are probabilistic representations of allowable sequences . This part:. Jianfeng Gao, MSR. (Joint work with . Jian. Huang, . Jiangbo. Miao, Xiaolong Li, Kuansan Wang and Fritz Behr). Outline. N-gram language model (LM) ABC. N-gram LM at Microsoft. Bing-It-On-. Ngram. Building Web scale N-gram LM. Conference on Empirical Methods in Natural Language . Processing 2007. 報告者：郝柏翰. 2013/06/04. Thorsten . Brants. , Ashok . C. . Popat. , . Peng. . Xu. , Franz . J. . Och. , Jeffrey Dean. Instructor: Paul Tarau, based on . Rada. . Mihalcea’s. original slides. Note. : some of the material in this slide set was adapted from an NLP course taught by Bonnie Dorr at Univ. of Maryland. Language Models. Data-Intensive Information Processing Applications ― Session #4. Jimmy Lin. University of Maryland. Tuesday, February 23, 2010. This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States. N-Gram Language Models ChengXiang Zhai Department of Computer Science University of Illinois, Urbana-Champaign 1 Outline General questions to ask about a language model N-gram language models Lecture 2: N-gram Kai-Wei Chang CS @ University of Virginia kw@kwchang.net Couse webpage: http://kwchang.net/teaching/NLP16 1 CS 6501: Natural Language Processing This lecture Language Models What are N-gram models? 21In the past ten years cognitive science has seen the rapid rise of interest in models, theories of the mind based on the interaction of large numbers of simple neuron-likeprocessing units. The appr Chapter 3. (3.1-3.4). Review. Text Normalization. Why?. How computationally?. Example tasks?. 2. Rule-based vs. Probabilistic. “. But it must be recognized that the notion of “probability of a sentence” is an entirely useless one, under any known interpretation of this term.” . Slides by . Shizhe Diao. and . Zoey. Li. Limitations. An example of a hallucination. ChatGPT describes the content of an article that does not exist. Source: . Wikipedia. Source: . The Harvard Gazette.

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