26. A method comprising: mining audio data from a source, to yield mined audio data; providing a bootstrap model, wherein the bootstrap model is based on text data of a website associated with a specific domain; and training a language model for call classification from the mined audio data based on the bootstrap model and a predetermined number of utterances not having a corresponding manual transcription data to yield a produced language model, the training being based on a geometrically computed n-tuple confidence score.
26. A method comprising: mining audio data from a source, to yield mined audio data; providing a bootstrap model, wherein the bootstrap model is based on text data of a website associated with a specific domain; and training a language model for call classification from the mined audio data based on the bootstrap model and a predetermined number of utterances not having a corresponding manual transcription data to yield a produced language model, the training being based on a geometrically computed n-tuple confidence score. 29. The method of claim 26 , further comprising: generating automatic speech recognition transcriptions using the produced language model; generating a new language model by applying an adaptation technique; and generating new automatic speech recognition transcriptions using the new language model.