Patent Document ID: 9489942
Application ID: 14759048

Base Claim:
1. A computerized statistical method for speech language understanding, performed by a processor in a computing apparatus, sequentially comprising: dialog act clustering including clustering spoken sentences based on similar dialog acts included in the spoken sentences; named entity clustering including extracting a group of named entity candidates from a result of the dialog act clustering, and clustering named entities based on context information around the extracted group of candidate named entities; and main act clustering including clustering main acts for each domain based on a result of the named entity clustering, wherein the named entity clustering extracts a group of candidate named entities using sources of words included in the spoken sentences, wherein when the group of candidate named entities includes a plurality of consecutive words, the plurality of consecutive words are segmented using a stickiness function.

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Claim 11:
11. The method of claim 1 , wherein the main act clustering is performed using a non-parametric Bayesian hidden Markov model, under conditions that the main act is a hidden state and words included in the spoken sentences, named entities extracted from the spoken sentences and system activities corresponding to the spoken sentences are observation values.