Abstract
The adequacies of three sets of acoustic measurements for stop consonant recognition were assessed by examining the performance of a trained human spectrogram reader in a stop identification task. The data sets consisted principally of(1) gray‐level pictures (wideband spectrograms); (2) two‐dimensional line drawings (LPC spectra and short‐time energy contours); and (3) tables of numerical measurements (e.g., frequencies, amplitudes, and bandwidths of spectral peaks). The reader's task was to identify the initial consonant in /CVb/ syllables selected from a corpus containing all combinations of the six stop consonants /b,d,g,p,t,k/ with the six vowels /i,e,ae,a,o,u/ as spoken by three male and three female talkers. The objective of the experiment was to identify an appropriate set of measurements for use in a knowledge‐based expert system for automatic stop consonant identification. Results of the experiment will be presented and discussed in the context of this objective.
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