A head-related transfer function model for fast synthesizing multiple virtual sound sources

A head-related transfer function(HRTF) model for fast and real-time synthesizing multiple virtual sound sources is proposed.Firstly,a HRIR(head-related impulse response,the time domain version of the HRTF) is decomposed by using a 2-level wavelet packet and then represented by a model composed of subband filters and reconstruction filters. The coefficients of the subband filters are the zero interpolation of the wavelet coefficients of the HRIR.The coefficients of the reconstruction filters can be calculated from the wavelet function.The model is simplified by applying a threshholding method to reduce the wavelet coefficients.The calculated results indicate that for a model with 30 wavelet coefficients, the error in reconstructed HRIR is about 1%.And the result of a psychoacoustic test shows that a model with 35 wavelet coefficients is indistinguishable from the original HRIR in hearing.When multiple virtual sound images are synthesized at the same time,the computational load of the proposed model is much less than the traditional HRTF filter.