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.