1. A computer-implemented method, comprising: a. aligning an utterance from a set of training data with a corresponding original transcription from the set of training data to produce a time-aligned transcription with time alignment information for each word in the utterance, wherein the set of training data includes transcription errors; b. decoding the same utterance with an incremental acoustic model and an incremental language model to produce a decoded transcription with time alignment information for each word; c. aligning the time-aligned and decoded transcriptions according to time alignment information; d. selecting all segments from the utterance having at least Q contiguous matching aligned words, where Q is a positive integer, by: including a silence in a selected segment comprising the Q matching aligned words when the selected segment is preceded or followed by a silence; and when there is no silence preceding or succeeding the selected segment: selecting the selected segment according to the original transcription with time alignment information; and inserting part of a silence segment from the beginning of the utterance into the beginning of the selected segment, and appending a part of a silence segment from the beginning of the utterance to the end of the selected segment; e. training the incremental acoustic model with the selected segments; and f. evaluating the accuracy of the incremental acoustic model built from the training data including transcription errors compared to the accuracy of an acoustic model built from a similar amount of training data having no transcription errors.
1. A computer-implemented method, comprising: a. aligning an utterance from a set of training data with a corresponding original transcription from the set of training data to produce a time-aligned transcription with time alignment information for each word in the utterance, wherein the set of training data includes transcription errors; b. decoding the same utterance with an incremental acoustic model and an incremental language model to produce a decoded transcription with time alignment information for each word; c. aligning the time-aligned and decoded transcriptions according to time alignment information; d. selecting all segments from the utterance having at least Q contiguous matching aligned words, where Q is a positive integer, by: including a silence in a selected segment comprising the Q matching aligned words when the selected segment is preceded or followed by a silence; and when there is no silence preceding or succeeding the selected segment: selecting the selected segment according to the original transcription with time alignment information; and inserting part of a silence segment from the beginning of the utterance into the beginning of the selected segment, and appending a part of a silence segment from the beginning of the utterance to the end of the selected segment; e. training the incremental acoustic model with the selected segments; and f. evaluating the accuracy of the incremental acoustic model built from the training data including transcription errors compared to the accuracy of an acoustic model built from a similar amount of training data having no transcription errors. 2. The computer-implemented method of claim 1 , comprising: dividing training data comprising audio data and transcription data corresponding to the audio data into N parts of M duration, wherein each part includes one or more utterances each comprising a plurality of words, and wherein N and M are positive integers; and g. iterating 1.a. through 1.f. for each utterance in one of the N parts; and h. iterating 2.g. for each of the N parts.