Statistical Language Model Trained With Semantic Variants
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Abstract
An intelligent query system for processing voiced-based queries is disclosed, which uses a combination of both statistical and semantic based processing to identify the question posed by the user by understanding the meaning of the user'"'"'s utterance. Based on identifying the meaning of the utterance, the system selects a single answer that best matches the user'"'"'s query. The answer that is paired to this single question is then retrieved and presented to the user. The system, as implemented, accepts environmental variables selected by the user and is scalable to provide answers to a variety and quantity of user-initiated queries.
121 Citations
41 Claims
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1-28. -28. (canceled)
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29. A method of generating a statistical language model (SLM) grammar for a task domain which includes semantically variant words and phrases, the method comprising the steps of:
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(a) providing a set of content words which can be associated with user questions in the task domain;
(b) determining semantic variants for each word in said set of content words;
wherein said semantic variants include at least synonyms;
(d) forming a semantic set of questions related to said user questions based on said synonyms;
(e) performing semantic decoding on said semantic set of questions, to identify a disambiguated set of questions;
(f) configuring n-gram probabilities for words and phrases in said SLM grammar based on said set of disambiguated questions;
wherein said SLM grammar is configured to recognize semantic variants of questions posed to a natural language speech recognition engine. - View Dependent Claims (30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40)
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41. A statistical language model (SLM) grammar for a task domain which includes semantically variant words and phrases comprising:
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(a) a set of content words which can be associated with user questions in the task domain;
(b) a set of semantic variants for each word in said set of content words;
wherein said semantic variants include at least synonyms;
(d) a disambiguated set of questions which are based on a semantic set of questions related to said user questions based on said synonyms;
wherein the SLM grammar includes n-gram probabilities for words and phrases which are configured based on said set of disambiguated questions;
and further wherein said SLM grammar is configured to recognize semantic variants of questions posed to a natural language speech recognition engine.
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Specification