15. A method of generating a statistical language model (SLM) grammar for a task domain which includes semantically variant words and phrases, comprising: using a computing system: determining semantic variants for each word in a set of content words associated with user questions in a task domain using a lexical dictionary, the semantic variants including at least synonyms; forming a semantic set of questions related to the user questions based on the semantic variants; performing semantic decoding on the semantic set of questions to identify a disambiguated set of questions; and configuring n-gram probabilities for words and phrases in the SLM grammar based on the set of disambiguated questions.
15. A method of generating a statistical language model (SLM) grammar for a task domain which includes semantically variant words and phrases, comprising: using a computing system: determining semantic variants for each word in a set of content words associated with user questions in a task domain using a lexical dictionary, the semantic variants including at least synonyms; forming a semantic set of questions related to the user questions based on the semantic variants; performing semantic decoding on the semantic set of questions to identify a disambiguated set of questions; and configuring n-gram probabilities for words and phrases in the SLM grammar based on the set of disambiguated questions. 17. The method of claim 15 , further comprising determining semantic variants for one or more phrases in the set of content words.