Short-time segments of the speech signal are analyzed in the spectral domain, and speaker models based on this information are built. These speaker models act as a clustered representation of the acoustic properties of a person鈥檚 voice and are thus characteristic for speakers with different kinds and degrees of pathologic conditions. The system is evaluated on two different data sets with speakers reading standardized texts. One data set contains 77 speakers after laryngeal cancer treated with partial removal of the larynx. The other data set contains 54 totally laryngectomized patients, equipped with a Provox shunt valve. Each speaker was rated by five expert listeners regarding three different criteria: strain, voice quality, and speech intelligibility.
We show correlations for each data set with r and 蟻 鈮?#xA0;0.8 between the automatic system and the mean value of the five raters. The interrater correlation of one rater to the mean value of the remaining raters is in the same range. We thus assume that for selected evaluation criteria, the system can serve as a validated objective support for acoustic voice and speech analysis.