Patent Document ID: 7835911
Application ID: 11324057

Base Claim:
1. A method for building a language model configuration comprising the steps of: categorizing a natural language understanding (NLU) application to produce an application categorization having a plurality of categories; classifying a corpus of example expressions to produce a classified corpus by identifying at least one of the categories for each example expression of the example expressions; and operating at least one computer configured with a plurality of instructions that, when executed, cause the at least one computer to train at least one statistical language model using said classified corpus by: building from the classified corpus a first language model configuration comprising a first statistical language model; evaluating an interpretation accuracy of the first language model configuration using test data; determining whether the evaluated interpretation accuracy of the first language model configuration is less than a desired accuracy; when it is determined that the evaluated interpretation accuracy of the first language model configuration is at least the desired accuracy, then adopting the first language model configuration; and when it is determined that the evaluated interpretation accuracy of the first language model configuration is less than the desired accuracy, then: sub-dividing the application categorization into a plurality of sub-categories; and building a second language model configuration comprising a plurality of statistical language models corresponding to the plurality of sub-categories.

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Claim 10:
10. The method of claim 1 , wherein: sub-dividing the application categorization into a plurality of sub-categories comprises sub-dividing the application categorization into a plurality of sub-categories at least one branch within said application categorization; building a second language model configuration comprising a plurality of statistical language models comprises: building a statistical language model for each of said at least one branch corresponding to the plurality of sub-categories; and saving a configuration file describing a sequential interconnection of each statistical language model of the plurality of statistical language models; and the method further comprises evaluating the interpretation accuracy of the second language model configuration by passing sentences of test data through said statistical language models of the second language model configuration in a sequence described by said configuration file.