1. A method for reducing the effect of an unknown signal bias in an input speech signal for use by a speech recognition system, comprising: (1) training the speech recognition system by using the following steps: (a) generating a set of centroids based on a training speech signal; (b) computing an estimate of the bias for the training speech signal based on maximizing a likelihood function; (c) subtracting the estimate of the bias from the training speech signal to obtain a tentative training speech value; (d) repeating steps (b) and (c), wherein each subsequent computed estimate of the bias is based on the previous tentative training speech value to arrive at a reduced bias training speech signal value; (e) recomputing the centroids based on the reduced bias training speech signal to generate a new set of centroids; (f) repeating steps (b) to (e) to compute a processed reduced bias speech signal and to form an enhanced set of centroids; (g) utilizing the enhanced set of centroids and the processed reduced bias speech signal as training input for a speech recognizer; (2) testing an input speech signal to minimize the unknown bias by using the following steps: (h) utilizing the enhanced set of centroids to compute an estimate of the bias for each utterance of the speech signal based on maximizing a likelihood function; (i) subtracting the estimate of the bias from the speech signal to obtain a tentative speech value; (j) repeating steps (h) and (i), wherein each subsequent computed estimate of the bias is based on the previous tentative speech value, resulting in a reduced bias speech signal value; and (3) utilizing the reduced bias speech signal as input to a speech recognizer.
1. A method for reducing the effect of an unknown signal bias in an input speech signal for use by a speech recognition system, comprising: (1) training the speech recognition system by using the following steps: (a) generating a set of centroids based on a training speech signal; (b) computing an estimate of the bias for the training speech signal based on maximizing a likelihood function; (c) subtracting the estimate of the bias from the training speech signal to obtain a tentative training speech value; (d) repeating steps (b) and (c), wherein each subsequent computed estimate of the bias is based on the previous tentative training speech value to arrive at a reduced bias training speech signal value; (e) recomputing the centroids based on the reduced bias training speech signal to generate a new set of centroids; (f) repeating steps (b) to (e) to compute a processed reduced bias speech signal and to form an enhanced set of centroids; (g) utilizing the enhanced set of centroids and the processed reduced bias speech signal as training input for a speech recognizer; (2) testing an input speech signal to minimize the unknown bias by using the following steps: (h) utilizing the enhanced set of centroids to compute an estimate of the bias for each utterance of the speech signal based on maximizing a likelihood function; (i) subtracting the estimate of the bias from the speech signal to obtain a tentative speech value; (j) repeating steps (h) and (i), wherein each subsequent computed estimate of the bias is based on the previous tentative speech value, resulting in a reduced bias speech signal value; and (3) utilizing the reduced bias speech signal as input to a speech recognizer. 2. The method of claim 1, wherein the speech recognition system utilizes a Hidden Markov Model speech recognizer.