The comparison of “Idiot's Bayes” and multivariate kernel-density in forensic speaker identification using Chinese vowel /a/
Huapeng Wang, Jun Jie Yang · 2010 3rd International Congress on Image and Signal Processing · 2010
The discriminant performance of likelihood ratios based on “Idiot's Bayes” approach and multivariate kernel density were examined on the speech of 21 male Chinese speakers using telephone recordings. The parameters used in this paper are formant central-frequencies, extracted from the Chinese vowel /a/. Experimental results show that the “Idiot's Bayes” approach provides a little stronger support for the same-speaker hypothesis and multivariate kernel density approach provides much stronger support for the different-speaker hypothesis; they both have good performance in Chinese vowel /a/.