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Efficient Approximation of Head-Related Transfer Functions in Subbands for Accurate Sound Localization.

Damián Marelli1, Robert Baumgartner2, Piotr Majdak2

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Summary

We developed four efficient algorithms to represent head-related transfer functions (HRTFs) in subbands, reducing computational load for virtual auditory displays. These methods maintain sound localization accuracy while significantly cutting processing demands.

Keywords:
Head-related transfer functions (HRTFs)sound localizationsparse approximationsubband signal processingvirtual acoustics

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Area of Science:

  • Acoustics
  • Signal Processing
  • Virtual Reality

Background:

  • Head-related transfer functions (HRTFs) are crucial for sound localization in virtual auditory displays.
  • Rendering complex virtual scenes with HRTFs is computationally intensive.

Purpose of the Study:

  • To propose four novel algorithms for efficient subband representation of HRTFs.
  • To minimize computational complexity while preserving perceptual HRTF properties.

Main Methods:

  • Developed four algorithms using sparse approximation for HRTF subband representation.
  • Optimized transfer matrices and filterbanks (FBs) individually and jointly.
  • Investigated latency-complexity trade-offs and psychoacoustic localization performance.

Main Results:

  • Proposed methods offer significant computational savings compared to existing approaches.
  • Identified approximation tolerances that avoid significant localization degradation.
  • Demonstrated effective HRTF representation in subbands.

Conclusions:

  • The novel subband HRTF representation algorithms efficiently reduce computational complexity.
  • These methods are suitable for real-time virtual auditory display applications.
  • Perceptual relevance and localization accuracy are maintained with the proposed approach.