Abstract: This paper introduces an automatic voice classification
system for the diagnosis of individual constitution based on Sasang
Constitutional Medicine (SCM) in Traditional Korean Medicine
(TKM). For the developing of this algorithm, we used the voices of
309 female speakers and extracted a total of 134 speech features from
the voice data consisting of 5 sustained vowels and one sentence. The
classification system, based on a rule-based algorithm that is derived
from a non parametric statistical method, presents 3 types of decisions:
reserved, positive and negative decisions. In conclusion, 71.5% of the
voice data were diagnosed by this system, of which 47.7% were
correct positive decisions and 69.7% were correct negative decisions.