1. A speech query recognition system comprising: a speech recognition engine for generating recognized words taken from an articulated speech utterance; and a natural language engine configured for processing said recognized words to generate at least two different types of search predicates for said articulated speech utterance; wherein said search predicates correspond to logical operators to be satisfied by a potential recognition match; a query formulation engine adapted to convert said recognized words and said search predicates into a structured query suitable for locating a set of one or more corresponding recognized matches for said articulated speech utterance; and said natural language engine further being configured for processing said set of one or more corresponding recognized matches to determine a final match for said articulated speech utterance using both semantic decoding and statistical based processing performed on said recognized words; wherein said semantic decoding is performed on entire word sentences contained in said articulated speech utterance to determine semantic variants of said word sentences in said one or more corresponding recognized matches, said semantic decoding being based on a term frequency calculation, which term frequency calculation is based on calculating a lexical distance between each word in said recognized words with each word of one or more topic query entries using a lexical dictionary.
1. A speech query recognition system comprising: a speech recognition engine for generating recognized words taken from an articulated speech utterance; and a natural language engine configured for processing said recognized words to generate at least two different types of search predicates for said articulated speech utterance; wherein said search predicates correspond to logical operators to be satisfied by a potential recognition match; a query formulation engine adapted to convert said recognized words and said search predicates into a structured query suitable for locating a set of one or more corresponding recognized matches for said articulated speech utterance; and said natural language engine further being configured for processing said set of one or more corresponding recognized matches to determine a final match for said articulated speech utterance using both semantic decoding and statistical based processing performed on said recognized words; wherein said semantic decoding is performed on entire word sentences contained in said articulated speech utterance to determine semantic variants of said word sentences in said one or more corresponding recognized matches, said semantic decoding being based on a term frequency calculation, which term frequency calculation is based on calculating a lexical distance between each word in said recognized words with each word of one or more topic query entries using a lexical dictionary. 15. The system of claim 1 , wherein both hyponyms and hypernyms are used for semantic decoding.