Speaker-independent recognition of stop consonants

Some experiments in stop consonant recognition using a new speech analysis technique are presented. The speech analysis technique used a Mellin-Fourier Homomorphism (MFH) on the Fourier transform of initial stop consonant bursts. A template-matching K-nearest neighbor algorithm, with MFH spectra as input, was used in identifying the stops. Extensive experiments using 32 speakers (8 each of male adults, female adults, male children, and female children) and 9 vowel environments were run. Recognition accuracies as high as 85% for voiced stops and 94% for unvoiced stops were achieved without any preliminary voicing decision.