Azimuth-dependent model of binaural speech transmission index based on near-field head-related transfer functions

Abstract

As well as the background noise and acoustic conditions of a given enclosed space, the binaural effect has a significant influence on the binaural speech transmission index (BSTI), especially for nearby sources. This effect can be quantitatively described by head-related transfer functions (HRTFs). As HRTFs are highly individual, the BSTIs from one person’s HRTF should differ from those of other people. However, this issue has rarely been studied. In the current work, we used the near-field HRTFs of 56 people to obtain the corresponding BSTIs, and analyzed the individual differences among them. The results show that the average standard deviation among the 56 individual BSTIs is almost within the just-noticeable-difference level of 0.03, and decreases with increasing sound source distance. We then acquired BSTIs from the KEMAR manikin and found that there were no significant differences with the median BSTIs across the 56 subjects. Thus, using the BSTIs of the KEMAR manikin, we developed regression BSTI models as a function of the azimuth based on seventh-order polynomial regression at different source distances.