1. A method for recognizing a spoken utterance from periodic samples of an electronic acoustic waveform, comprising automatically: (a) determining upper and lower bounding frequencies and amplitudes of profiled waves extracted from each sample; (b) grouping samples as posture spectra and changing spectra; (c) calculating beat prominences of posture and changing spectra from amplitudes of profiled waves; (d) identifying syllables from patterns of posture and changing spectra and beat prominences; (e) calculating syllable prominences from beat prominences; (f) identifying words from syllable patterns and syllable prominences; and (g) storing electronically a series of data entries, each data entry identifying words of the spoken utterance.
1. A method for recognizing a spoken utterance from periodic samples of an electronic acoustic waveform, comprising automatically: (a) determining upper and lower bounding frequencies and amplitudes of profiled waves extracted from each sample; (b) grouping samples as posture spectra and changing spectra; (c) calculating beat prominences of posture and changing spectra from amplitudes of profiled waves; (d) identifying syllables from patterns of posture and changing spectra and beat prominences; (e) calculating syllable prominences from beat prominences; (f) identifying words from syllable patterns and syllable prominences; and (g) storing electronically a series of data entries, each data entry identifying words of the spoken utterance. 5. The method of claim 1 wherein step (c) comprises calculating the average of the amplitudes of the profiled waves in each posture group and each changing group and using the average as the beat prominence of the respective group.