Genetic algorithm approach to head-related transfer functions modeling in 3-D sound system

Head-related transfer functions, or HRTFs, refer to the spectral filtering from sound sources to listeners´ eardrums. It is an important cue to spatial hearing. Since HRTFs vary as a function of relative source locations and subjects, practical implementation of 3D audio always races a large set of HRTFs for different azimuths and elevations (even if non-individualized HRTFs are used). Previous works have proposed several models to represent the HRTFs in order to achieve data reduction. In this paper, we describe our work In applying Genetic Algorithm (GA) to HRTF modeling. Based on a linear combination model, our system uses a GA to find the basis spectra and the normal equation method to compute the weights matrix. Individual HRTFs at different azimuths and elevations are represented as a weighted combination of the basis spectra. A set of HRTFs from the MIT Media Lab´s KEMAR measurements was used as the source data