Efficient relative transfer function estimation framework in the spherical harmonics domain

Abstract

In acoustic conditions with reverberation and coherent sources, various spatial filtering techniques, such as the linearly constrained minimum variance (LCMV) beamformer, require accurate estimates of the relative transfer functions (RTFs) between the sensors with respect to the desired speech source. However, the time-domain support of these RTFs may affect the estimation accuracy in several ways. First, short RTFs justify the multiplicative transfer function (MTF) assumption when the length of the signal time frames is limited. Second, they require fewer parameters to be estimated, hence reducing the effect of noise and model errors. In this paper, a spherical microphone array based framework for RTF estimation is presented, where the signals are transformed to the spherical harmonics (SH)-domain. The RTF time-domain supports are studied under different acoustic conditions, showing that SH-domain RTFs are shorter compared to conventional space-domain RTFs.