1. A computer-implemented method comprising: forming a statistically derived mapping based on measured statistics from speech utterances received during off-line processing and feature normalization parameters associated with the speech utterances, wherein each measured statistic is based on portion of a single speech utterance and each feature normalization parameter is based on multiple speech utterances, wherein the speech utterances received during off-line processing are received from a speech database that includes utterances of multiple speakers in multiple acoustic environments and wherein forming the statistically derived mapping comprises determining weights by statistical regression that relate the measured statistics from the speech utterances received during off-line processing to the associated feature normalization parameters; measuring statistics of energy, from an initial portion of a speech utterance received during on-line processing, where the initial portion of the speech utterance includes a limited number of speech frames having cepstral features and estimated to comprise a minimum and maximum energy to provide estimates of signal and noise levels; and estimating feature normalization parameters for the speech utterance received during on-line processing based on the measured statistics of the initial portion of a speech utterance by linearly mapping the cepstral features and the signal and noise levels using the statistically derived mapping weights.
13. The method of claim 1 , wherein the statistically derived mapping is a linear map.