2. A computer-implemented method, comprising: accessing a literal speech recognition corpus comprising a plurality of expressions, an expression comprising a sequence of word tokens; accessing a concept tagging module for identifying instances of a plurality of concepts within an expression and for replacing expressions with placeholders that indicate classes associated with concepts; generating a parameterized speech recognition corpus by using the concept tagging module to identify, within the expressions of the literal speech recognition corpus, portions of the expressions that are instances of the concepts and to replace the identified portions of the expressions with placeholders; and generating a parameterized statistical model based on the parameterized speech recognition corpus receiving, over a computer network, an utterance of a user, the utterance having been accepted from the user at a client device as spoken input; and generating a text interpretation of the utterance using the parameterized statistical model together with a language sub-model corresponding to one of the plurality of concepts.
2. A computer-implemented method, comprising: accessing a literal speech recognition corpus comprising a plurality of expressions, an expression comprising a sequence of word tokens; accessing a concept tagging module for identifying instances of a plurality of concepts within an expression and for replacing expressions with placeholders that indicate classes associated with concepts; generating a parameterized speech recognition corpus by using the concept tagging module to identify, within the expressions of the literal speech recognition corpus, portions of the expressions that are instances of the concepts and to replace the identified portions of the expressions with placeholders; and generating a parameterized statistical model based on the parameterized speech recognition corpus receiving, over a computer network, an utterance of a user, the utterance having been accepted from the user at a client device as spoken input; and generating a text interpretation of the utterance using the parameterized statistical model together with a language sub-model corresponding to one of the plurality of concepts. 5. The computer-implemented method of claim 2 , wherein the interpretation comprises a lattice in which nodes of the lattice are literal word tokens and edges between the nodes have weights indicating probabilities that the corresponding literal word tokens occur in sequence.