Patent Document ID: 8700403
Application ID: 11266867

Base Claim:
1. A computer-implemented method for modeling spoken language for a conversational dialog system, comprising: modeling, by a computer processor, dependency relations of the spoken language via a probabilistic dependency model; incorporating, by the computer processor, Gaussian priors during feature selection and during parameter optimization; parsing, by the computer processor, a sequence of words, the parsing including systematically searching through pairs of head words bottom-up using a chart parsing technique; and at each step in the search, computing, by the computer processor, the probabilistic scores for each pair based on the probabilistic dependency model and keeping n best candidate pairs for each region; wherein the dependency model is decomposed into a model for a first sub-region, a second sub-region, and a component which includes a last dependency relation that connects the first and second sub-regions, with an adjustment of mutual information between the last dependency relation and the first and second sub-regions.

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Claim 11:
11. The method of claim 1 , wherein: the dependency model for a region L i,j extending between word i and word j is calculated as P( L i,j )=P( L i,k )*P( L k+1,j )*P(L i,j | L i,k , L k+1,j )*e MI( L i,k , L k+1,j ) ; (i, k) is a first sub-region of the region L i,j ; (k+ 1 , j) is a second sub-region of the region L i,j ; L i,j is a triple of 1 i,j , W i,k , and W k+1,j ; 1 i,j is a last dependency relation that connects the first and second sub-regions; W i,k is a head word representing the first sub-region; and W k+1,j is a head word representing the second sub-region.