1. A method for automatic speech recognition, the method comprising: determining for an input signal a plurality of scores representative of certainties that the input signal is associated with corresponding states of a speech recognition model; using the speech recognition model and the determined scores to compute an average signal; computing, via a processor device executing instructions, a difference value representative of a difference between the input signal and the average signal; and processing, via the processor device, the input signal in accordance with the difference value; wherein computing the average signal comprises: identifying a given score from the plurality of scores; selecting from the plurality of scores a set of scores whose corresponding values are within a predetermined threshold from a value of the given score; and performing an averaging operation on observation mean vectors of observation densities associated with the selected plurality of scores to obtain the average signal.
1. A method for automatic speech recognition, the method comprising: determining for an input signal a plurality of scores representative of certainties that the input signal is associated with corresponding states of a speech recognition model; using the speech recognition model and the determined scores to compute an average signal; computing, via a processor device executing instructions, a difference value representative of a difference between the input signal and the average signal; and processing, via the processor device, the input signal in accordance with the difference value; wherein computing the average signal comprises: identifying a given score from the plurality of scores; selecting from the plurality of scores a set of scores whose corresponding values are within a predetermined threshold from a value of the given score; and performing an averaging operation on observation mean vectors of observation densities associated with the selected plurality of scores to obtain the average signal. 21. The method as in claim 1 , wherein the scores are probability scores associated with states of the input signal and wherein the average signal is a moving average generated based on the input signal, the method further comprising: biasing scores of noise states associated with the speech recognition model to increase a probability that a segment of the input signal is deemed to be sound received on a noise channel rather than sound received on a speech channel.