HRTF-Based Sound Field Interpolation in the Presence of a Human Head

Sammanfattning: There are different ways of evaluating the sound pressure in a sound field. Doing so is an essential part of several applications, such as active sound control and voice analysis. One way of evaluating the sound pressure in a sound field is by measuring a few discrete points in the field, combined with an interpolation method to find the sound pressure for the remaining field. Recently, it has been shown that kernel ridge regression (KRR) can accurately interpolate a sound field from discrete points in space. This report examines the effect of inaccurate measurements for the resulting estimated sound field by adding noise in all measurements. Further, to allow for accurate estimation of how a sound is perceived at a given location, one not only needs to form an estimate of the expected sound field at the location, but also to examine how the presence of the person's head will shape the resulting field. Thus, the use of a pre-calibrated head-related transfer function (HRTF) in combination with the interpolation technique to interpolate the in-ear sound field is also proposed. Using both simulated and anechoic audio data, the effect of different kernels as well as the added noise for the sound field estimate is studied, which is then illustrating how the combined sound field interpolation technique allows for an improved estimate of the sound field, for all frequencies. Finally, the combined sound field interpolation is shown to be more effective than the KRR method, for both the simulated and the anechoic audio data, with the presence of a person in the sound field.