1. A method comprising: receiving speech recognition output associated with speech from a user; receiving an error model characterizing how automatic speech recognition transcription errors are made; generating, via a processor, guesses of a true transcription based on an error model-based algorithm, wherein the error model-based algorithm uses the error model and the speech recognition output; and generating, based on the guesses of the true transcription, a personalized user model associated with a user voiceprint of the user, wherein the generating of the personalized user model comprises iteratively guessing the true transcription until a threshold is met.
1. A method comprising: receiving speech recognition output associated with speech from a user; receiving an error model characterizing how automatic speech recognition transcription errors are made; generating, via a processor, guesses of a true transcription based on an error model-based algorithm, wherein the error model-based algorithm uses the error model and the speech recognition output; and generating, based on the guesses of the true transcription, a personalized user model associated with a user voiceprint of the user, wherein the generating of the personalized user model comprises iteratively guessing the true transcription until a threshold is met. 2. The method of claim 1 , wherein generating of the guesses further comprises repeating, until a threshold is met, steps comprising: guessing the true transcription from a current guess of the personalized user model, to yield a current guess of the true transcription; and guessing the personalized user model based on the current guess of the true transcription.