1. A method of tuning a speech system comprising: accessing, from a database, information representing a plurality of utterances for at least one speech-enabled application, the plurality of utterances comprising at least a first type of utterance and a second type of utterance; accessing, from the database, interpretive information representing an assigned interpretation for at least a portion of the plurality of utterances; determining, by a training tool subsystem, an appropriate interpretation for the portion of the plurality of utterances; comparing, by the training tool subsystem, the assigned interpretation for the portion of the plurality of utterances to the appropriate interpretation for the portion of the plurality of utterances; determining, by the training tool subsystem, a frequency value for the second type of utterance that represents the percentage of occurrence of the second type of utterance in the plurality of utterances; determining, by the training tool subsystem, that the speech-enabled application more accurately responds to the first type of utterance; and electing, by the training tool subsystem, to apply a targeted tuning to the speech-enabled application to improve recognition of the second type of utterance when the frequency value for the second type of utterance is greater than a frequency threshold value.
1. A method of tuning a speech system comprising: accessing, from a database, information representing a plurality of utterances for at least one speech-enabled application, the plurality of utterances comprising at least a first type of utterance and a second type of utterance; accessing, from the database, interpretive information representing an assigned interpretation for at least a portion of the plurality of utterances; determining, by a training tool subsystem, an appropriate interpretation for the portion of the plurality of utterances; comparing, by the training tool subsystem, the assigned interpretation for the portion of the plurality of utterances to the appropriate interpretation for the portion of the plurality of utterances; determining, by the training tool subsystem, a frequency value for the second type of utterance that represents the percentage of occurrence of the second type of utterance in the plurality of utterances; determining, by the training tool subsystem, that the speech-enabled application more accurately responds to the first type of utterance; and electing, by the training tool subsystem, to apply a targeted tuning to the speech-enabled application to improve recognition of the second type of utterance when the frequency value for the second type of utterance is greater than a frequency threshold value. 16. The method of claim 1 , farther comprising setting an utterance type-specific hit rate design threshold for each of a collection of expected utterance types, wherein the targeted tuning comprises exclusively tuning the speech-enabled application to utterance types having an actual utterance type specific hit rate that fails to reach a respective utterance type-specific hit rate design threshold.