Usage of Spectral Distortion for Objective Evaluation of Personalized HRTF in the Median Plane

Abstract

Measuring the head-related transfer functions (HRTFs) for each subject is a complex process. Therefore, it is necessary to develop procedures that allow the estimation of personalized HRTFs. It is common to estimate the weights of the principal component analysis (PCA) of a group of subjects based on some anthropometric parameters using multivariable regression modelling. Moreover, to objectively evaluate the goodness of fit} between the original HRTFs and the personalized ones, the spectral distortion (SD) is usually used too. However, its suitability in the median plane, in which the spectral profiles are crucial to localize a sound source, has not yet been demonstrated. This paper analyses the validity of the SD as a measure of the quality of the HRTF personalization in the median plane, from the localization point of view. The HRTFs were modelled from the weights estimated by multiple linear regression and artificial neural networks (ANNs). The SD was used to compare the HRTFs measured with those estimated. Likewise, the level of fitting accuracy of characteristic resonance and notches in the median plane was also compared. Despite the fact that the SD scores of ANNs are lower than those of the multiple linear regression and are similar to those reported by other studies, the errors obtained from analysing both central frequencies and levels for resonance and notches could be discriminated.