9. A system comprising: a processor; an automatic speech recognizer configured to control the processor to automatically transcribe utterance data not having a corresponding manual transcription based on a bootstrap model and produce a set of automatically transcribed data, wherein the bootstrap model is based on text data mined from a website relevant to a specific domain; a learning module configured to control the processor to select a predetermined number of utterances from the set of automatically transcribed data based on a geometrically computed n-tuple confidence score to yield a selected number of utterances, the selected number of predetermined utterances to be manually transcribed, added to a set of manually transcribed data, and deleted from the set of automatically transcribed data; a training module configured to control the processor to train a language model using the set of manually transcribed data and the set of automatically transcribed data; and a labeler to label a portion of one of the set of automatically transcribed data and the set of manually transcribed data.
9. A system comprising: a processor; an automatic speech recognizer configured to control the processor to automatically transcribe utterance data not having a corresponding manual transcription based on a bootstrap model and produce a set of automatically transcribed data, wherein the bootstrap model is based on text data mined from a website relevant to a specific domain; a learning module configured to control the processor to select a predetermined number of utterances from the set of automatically transcribed data based on a geometrically computed n-tuple confidence score to yield a selected number of utterances, the selected number of predetermined utterances to be manually transcribed, added to a set of manually transcribed data, and deleted from the set of automatically transcribed data; a training module configured to control the processor to train a language model using the set of manually transcribed data and the set of automatically transcribed data; and a labeler to label a portion of one of the set of automatically transcribed data and the set of manually transcribed data. 13. The system of claim 9 , wherein: the automatic speech recognizer, the learning module, and the training module are configured to control the processor to work together repeatedly, until word accuracy converges, to: using the language model, automatically transcribe utterance data not having a corresponding manual transcription and produce a set of automatically transcribed data, select a predetermined number of utterances from the set of automatically transcribed data to be manually transcribed, added to the set of manually transcribed data, and deleted from the set of automatically transcribed data, and train a second language model using the set of manually transcribed data and the set of automatically transcribed data, wherein the second language model is used as the language model for each subsequent repetition.