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CHAPTER N-gram Language Models

Speech and Language Processing. Daniel Jurafsky & James H. Martin. Copyright 2021. Allrights reserved. Draft of December 29, Language Models You are uniformly charming! cried he, with a smile of associating and nowand then I bowed and they perceived a chaise and four to wish sentence generated from a Jane Austen trigram modelPredicting is difficult especially about the future, as the old quip goes. But howabout predicting something that seems much easier, like the next few words someoneis going to say? What word, for example, is likely to followPlease turn your homework ..Hopefully, most of you concluded that a very likely word isin, or possiblyover,but probably notrefrigeratororthe. In the following sections we will formalizethis intuition by introducing Models that assign aprobabilityto each possible nextword.

simpler than state-of-the art neural language models based on the RNNs and trans-formers we will introduce in Chapter 9, they are an important foundational tool for understanding the fundamental concepts of language modeling. 3.1 N-Grams Let’s begin with the task of computing P(wjh), the probability of a word w given some history h.

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