An Algorithm for Efficiently Synthesizing Multiple Near-Field Virtual Sources in Dynamic Virtual Auditory Display
An algorithm for efficiently synthesizing multiple near-field virtual sources in dynamic virtual auditory display (VAD) is proposed. Applying the method of principal component analysis, a set of measured near-field head-related impulse responses (HRIRs) for KEMAR manikin at various source directions and distances are decomposed into a weighted sum of fifteen time-domain basis functions along with a mean time-domain function, in which the time-independent weights represent the location dependence of HRIRs. Accordingly, multiple virtual sources synthesis at various locations is implemented by a common bank of sixteen filters representing the time -domain basis functions and the mean time-domain function, in which the adjustable gains of the filters for each input stimulus (as well as an overall gain and delay for each input stimulus) control intended source locations. The computational cost of the proposed algorithm is reduced compared with that of conventional ones. Psychoacoustic experiments via a dynamic VAD with head-tracking validate the performance of the proposed algorithm.
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