22. A non-transitory computer-readable medium comprising one or more computer-executable modules, the one or more computer-executable modules configured to: receive an identification of a desired training utterance having a first portion and a second portion, wherein the desired training utterance is not included in a corpus; select, from the corpus, a first utterance comprising at least a first portion of the desired training utterance; extract, from the first utterance, a portion of the first utterance comprising the first portion of the desired training utterance, wherein the first portion of the desired training utterance and at least the portion of the first utterance are associated with a first desired characteristic; select, from the corpus, a second utterance comprising at least a second portion of the desired training utterance; extract, from the second utterance, a portion of the second utterance comprising the second portion of the desired training utterance, wherein the second portion of the desired training utterance and at least the portion of the second utterance are associated with a second desired characteristic; concatenating at least the portion of the first utterance the portion of the second utterance to generate the desired training utterance; and train an acoustic model using the desired training utterance that is generated.
22. A non-transitory computer-readable medium comprising one or more computer-executable modules, the one or more computer-executable modules configured to: receive an identification of a desired training utterance having a first portion and a second portion, wherein the desired training utterance is not included in a corpus; select, from the corpus, a first utterance comprising at least a first portion of the desired training utterance; extract, from the first utterance, a portion of the first utterance comprising the first portion of the desired training utterance, wherein the first portion of the desired training utterance and at least the portion of the first utterance are associated with a first desired characteristic; select, from the corpus, a second utterance comprising at least a second portion of the desired training utterance; extract, from the second utterance, a portion of the second utterance comprising the second portion of the desired training utterance, wherein the second portion of the desired training utterance and at least the portion of the second utterance are associated with a second desired characteristic; concatenating at least the portion of the first utterance the portion of the second utterance to generate the desired training utterance; and train an acoustic model using the desired training utterance that is generated. 26. The non-transitory computer-readable medium of claim 22 , wherein the corpus comprises utterances from at least one of audiobooks, movie soundtracks, customer service calls or speeches.