9. The system of claim 7 , further comprises: means for aligning frames of the normalized original waveform and frames of each synthetic waveform to a corresponding one of the N textual transcriptions; and means for calculating the distance measure between the normalized original waveform and each of the synthetic waveforms based on the corresponding alignments.
7. An automatic speech recognition system, comprising: a decoder for decoding an original waveform of acoustic utterances to produce N textual transcriptions, the N textual transcriptions representing N-best textual transcription hypotheses of the decoded original waveform; a text to speech system generating a synthetic waveform for each of the N textual transcriptions; a means to perform a speaker normalization on the original waveform to match vocal-tract characteristics of a speaker from whose data the TTS is derived; and a comparator for comparing scores based on an overall distance measure between each synthetic waveform and the normalized original waveform, an acoustic model score of a corresponding textual transcription of the synthetic waveform, and a language model score of the corresponding textual transcription to determine a corresponding one of the N-best textual transcriptions to output, wherein the overall distance measures are computed by a processor: computing a distance measure between the synthetic waveform and the normalized original waveform; and summing the distance measures to generate an overall distance measure representing a distance between the normalized original waveform and the synthetic waveform, and wherein N is greater than 1.