LPC peak weighted spectral matching measures

Abstract This report proposed an LPC peak weighted spectral matching measure, a voice recognition method with weighted global spectral peaks (formants), and demonstrates its usefulness by comparing it with the conventional LPC matching measure. The “peak weighted measure” is defined by the integral of the product Kw , where K is a function representing spectral differences between the standard pattern and input voice and w is a weighted function representing peaks. It is shown that the integral value can be computed simply by LPC analysis parameters. Analysis of the weighted spectral difference Kw shows some variation in effectiveness of peak weighting. Experiments on vowel discrimination to evaluate the measure conclude that the discrimination error rate of 11.7% in the conventional LPC matching measure can be reduced to 9.3% by using the peak weighted measure and, especially, it is remarkably improved for the vowels /a/, /u/, /o/. Further, the variance of the discrimination error rates by speakers is smaller than that of the conventional LPC matching measure.