Method and system for automatically building natural language understanding models

Abstract

The invention disclosed herein concerns a system () and method () for building a language model representation of an NLU application. The methodcan include categorizing an NLU application domain (), classifying a corpus in view of the categorization (), and training at least one language model in view of the classification (). The categorization produces a hierarchical tree of categories, sub-categories and end targets across one or more features for interpreting one or more natural language input requests. During development of an NLU application, a developer assigns sentences of the NLU application to categories, sub-categories or end targets across one or more features for associating each sentence with desire interpretations. A language model builder () iteratively builds multiple language models for this sentence data, and iteratively evaluating them against a test corpus, partitioning the data based on the categorization and rebuilding models, so as to produce an optimal configuration of language models to interpret and respond to language input requests for the NLU application.