1. In a voice recognition system, a method comprising the steps of: sampling a voice signal; applying a Fourier transform to a plurality of frame intervals of the sampled voice signal to generate spectral data having a spectral envelope for each of the plurality of frame intervals; subdividing the spectral data for each of the plurality of frame intervals into a plurality of bands; filtering out the spectral envelope from the spectral data of each of the plurality of frame intervals to generate filtered spectral data for each of the plurality of frame intervals; applying a Fourier transform to the filtered spectral data for each of the plurality of bands to generate an autocorrelation function for each of the plurality of bands; measuring a value of the magnitude of the autocorrelation function for each of the plurality of bands, whereby the value is a measure of a degree of voiceness for each of the plurality of bands; applying the degree of voiceness for each of the plurality of bands to a corresponding plurality of phoneme models; and deriving a textual equivalent of speech from the voice signal by searching through a phoneme library according to predictions made by the corresponding plurality of phoneme models.