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The proposed hierarchial grammar model is indeed a weighted concept transition network which combines grammar with a method similar to the probability distribution in statistical language model. The smoothing method that assigns minor probabilities for out-of-grammar and OOV phrases is used to make the model robust. The experiments demonstrate that the hierarchial flexible and simple grammar model can decrease language model's perplexity and improve the predictive performance, The accuracy rate can be raised by using the language model in the predictions for speech recognition. [ABSTRACT FROM AUTHOR]