Mechanism for generating peaks and notches of head-related transfer functions in the median plane

Abstract

It has been suggested that the first spectral peak and the first two spectral notches of head-related transfer functions (HRTFs) are cues for sound localization in the median plane. Therefore, to examine the mechanism for generating spectral peaks and notches, HRTFs were calculated from four head shapes using the finite-difference time-domain method. The comparison between HRTFs calculated from the whole head and the pinna-related transfer functions calculated from the segmented pinna indicated that the pinna determines the basic peak-notch pattern of the HRTFs. An analysis of the distribution patterns of pressure nodes and anti-nodes on the pinna computed in the steady state for sinusoidal excitations confirmed that the first three peaks correspond to the first three normal modes of the pinna. The analysis also revealed that at the first spectral notch frequencies, one or two anti-nodes appeared in the cymba and the triangular fossa, and a node developed in the concha. Furthermore, according to changes in the instantaneous pressure distribution patterns on the pinna, three types of mechanisms were hypothesized for inducing the node in the concha depending on the source elevation angle.

On the authenticity of individual dynamic binaural synthesis

“…26 Regularization was used to limit filter gains if perceptually required: HpTFs typically show distinct notches at high frequencies which are most likely caused by anti-resonances of the pinna cavities. 33 For an example see Fig. 2 (top) at approximately 10 and 16 kHz.…”

Personalization of head-related transfer functions in the median plane based on the anthropometry of the listener's pinnae

“…The boundary element method (BEM) has been used to calculate HRTFs in a number of studies (Katz, 2001;Kahana and Nelson, 2006;Kreuzer et al, 2009). The results of numerical calculations by the finite-difference time-domain (FDTD) method, which is much faster than the BEM, revealed that the fundamental spectral feature of the HRTF of an individual listener can be calculated from the baffled pinna (Takemoto et al, 2012). At the present, however, neither the BEM nor the FDTD method is available for ordinary listeners because special equipment, e.g., a functional magnetic resonance imaging system, is required to digitize the complicated shape of the pinnae of an individual listener.…”

Influence of voxelization on finite difference time domain simulations of head-related transfer functions

“…For DX ¼ 2.35 mm, axial and diagonal wave packets with f max ¼ 12.18 kHz will almost be in antiphase (E s g ¼ 48%). While such scenarios are unlikely to substantially affect the not-fully-understood mechanism 17 that generates spectral cues, uncertainty still persists. Therefore, the analyzed bandwidth is considered a parameter in the analysis.…”

“…Nonetheless, the reported variance issue is expected to become insignificant as the voxel is greatly reduced in size. It is noted that similar issues may arise when the voxel-based geometry results from an MRI scan; although the geometry-grid misalignment of the geometry is less of an issue due to the reduced grid sizes generally used, 15,17 either scanner parameters or voxel processing algorithms may influence the FDTD-simulated acoustic field significantly.…”

“…A variety of simulation methods have been employed to simulate HRTFs: the boundary element method, [9][10][11] the finite element method, 12 the adaptive rectangular decomposition method 13 and the finite-difference timedomain method. [14][15][16][17] However, simulations also have specific limitations, constraints and parameters that affect the resulting HRTFs such that the consistency with measured HRTFs is affected 15,18 by inaccuracies in both frameworks. In the case of Finite Difference Time Domain (FDTD) simulations, there are many factors influencing the computed sound field independent of the actual numerical simulation.…”