Perplexity of n-gram and dependency language models

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Dependency LM Examples of additional context information ● Model Tp,wp coarse-grained POS tag of parent, word form of parent P( The dog barked again ) = P( The | N, dog ) · P( dog | V, barked ) · P( barked | x, NONE ) · P( again | V, barked ) The dog barked again 34
Dependency LM Examples of additional context information ● Model E,C,wp,N edge direction, # children, word form of parent, word is N th child of its parent P( The dog barked again ) = P( The | right, 0, dog , 1) · P( dog | right, 1, barked , 1) · P( barked | left, 2, NONE , 1) · P( again | left, 0, barked , 2) The dog barked again 35
Page 1 and 2: Perplexity of n-gram and dependency
Page 3 and 4: P(s) = ? Language Models - basics P
Page 5 and 6: Language Models - basics P(s) = P(w
Page 13 and 14: Language Models - design decisions
Page 15 and 16: Language Models - design decisions
Page 17 and 18: Post-ngram LM In general: P(s) = P(
Page 19 and 20: Post-ngram LM In general: P(s) = P(
Page 21 and 22: Dependency LM ● exploit the topol
Page 23 and 24: Dependency LM ● exploit the topol
Page 25 and 26: Dependency LM Motivation for usage
Page 27 and 28: ● Model wp word form of parent P(
Page 29 and 30: ● Model E,wp edge direction, word
Page 31 and 32: ● Model N,wp the word is N th chi
Page 33: Dependency LM Examples of additiona
Page 37 and 38: Evaluation ● Train and test data
Page 39 and 40: Findings confirmed for all seven la
Page 41: Thank you 41

Perplexity of n-gram and dependency language models

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