providing an input HRTF data set as input into a network, which comprises basis filters, wherein the input HRTF data set includes a corresponding set of HRTF filters for each location in a set of locations;

for each respective location in the set of locations, causing the network to use the input HRTF data set to iteratively learn approximation data comprising the following: (i) corresponding mixing channel gains that are used to control input to the mixing channels, (ii) coefficients that are used to control the FIR filters, and (iii) shapes of the basis filters; and

storing a correlation between each location in the set of locations and specific values selected from the approximation data, wherein, by subsequently selecting a particular location in the set of locations, a corresponding set of values from the approximation data are also selected, said corresponding set of values include specific mixing channel gains, the coefficients, and the basis filter shapes.