Abstract
The head related transfer function (HRTF) method of providing spatial sound images has not been capable of dealing with individual differences between human listeners yet. The HRTF varies from person to person and with the direction of the sound source. We focus on this directional variation of the individual HRTF. Principal component analysis is applied to draw the loci of the variation in an orthogonal basis space. Each locus corresponds to a single individual HRTF, and the loci are utilized for clustering the individual HRTF. Some typical ones can be extracted from clusters; we show that they are useful in compensating for the individual differences found in HRTFs.
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