10. A method of providing reading tutoring, comprising: receiving a textual indication of a story; building a target context free grammar at runtime based on a portion of the textual indication; obtaining a garbage model that is indicative of a list of words in a general domain; prompting a user for an utterance; providing a received acoustic signal of the user's utterance to a speech recognition engine; comparing an output from the speech recognition engine to the target context free grammar; comparing an output from the speech recognition engine to at least a portion of the garbage model; storing an indication of the comparison to at least one of the target context free grammar and the garbage model in a data store including an indication of the user who provided the utterance; utilizing a miscue engine to identify a miscue based on the comparison to at least one of the target context free grammar and the garbage model, wherein identifying the miscue comprises identifying a miscue selected from a group consisting of a stop, a pause, a mispronunciation and a partial pronunciation; reporting progress of the user based at least in part on the stored indication; and wherein reporting progress comprises reporting the miscue.
10. A method of providing reading tutoring, comprising: receiving a textual indication of a story; building a target context free grammar at runtime based on a portion of the textual indication; obtaining a garbage model that is indicative of a list of words in a general domain; prompting a user for an utterance; providing a received acoustic signal of the user's utterance to a speech recognition engine; comparing an output from the speech recognition engine to the target context free grammar; comparing an output from the speech recognition engine to at least a portion of the garbage model; storing an indication of the comparison to at least one of the target context free grammar and the garbage model in a data store including an indication of the user who provided the utterance; utilizing a miscue engine to identify a miscue based on the comparison to at least one of the target context free grammar and the garbage model, wherein identifying the miscue comprises identifying a miscue selected from a group consisting of a stop, a pause, a mispronunciation and a partial pronunciation; reporting progress of the user based at least in part on the stored indication; and wherein reporting progress comprises reporting the miscue. 13. The method of claim 10 , and further comprising: providing an acoustic model that is trained for use in the speech recognition engine, wherein the data for training the acoustic model includes data from a plurality of children.