Abstract
The principal object in using a phonetic approach is the reduction of the influence on recognition rate caused by the intra- and inter-speaker speech variations. The system is implemented on a 16-K minicomputer and uses a filter bank delivering spectral sections, 0–5 kHz, every 10 ms. Estimates of the first three formants are calculated and energies in different spectral bands are used to segment the speech signal into broad classes. The following measures are calculated depending on the segmental class and the speech parameter: mean values, steady-state values, durations, transition rates, and some distances between formants. In a learning phase the statistics of the measures of the used vocabulary are automatically calculated by a program given the quasiphonetic spelling of the input words. The statistics are based on phoneme pairs, i.e., diphones. In the recognition phase the program uses the statistics and the quasiphonetic spelling to recognize the input words. Six male speakers were used for calculating the statistics of a 41-word vocabulary. Their mean recognition rate was 98%, using a new recording. The rate decreased to 96.3% using four male talkers, unknown to the system. [Work supported by STU, Sweden.]
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