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The dynamic gammawarp auditory filterbank.

James M Kates1, Shashidhar Prabhu2

  • 1Department of Speech Language and Hearing Sciences, University of Colorado, Boulder, Colorado 80309, USA.

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A new gammawarp filterbank offers a faster implementation of dynamic compressive gammachirp (dcGC) auditory filters. This computationally efficient method improves speech intelligibility and quality predictions for both normal and impaired hearing.

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Area of Science:

  • Auditory signal processing
  • Digital filter design
  • Speech perception research

Background:

  • Auditory filterbanks are crucial for speech intelligibility and quality metrics.
  • Existing dynamic compressive gammachirp (dcGC) models require computationally intensive implementations.
  • Accurate modeling of auditory filter shapes and hearing loss impacts is essential.

Purpose of the Study:

  • To present an alternative, computationally efficient implementation of the dynamic compressive gammachirp (dcGC) auditory filterbank.
  • To introduce the gammawarp filterbank, utilizing digital frequency warping.
  • To enhance the speed of dcGC filterbank implementations for practical applications.

Main Methods:

  • Implemented a gammawarp filterbank using digital frequency warping instead of cascaded second-order sections.
  • Constrained warped finite impulse response filter coefficients to be symmetrical, ensuring identical phase responses across the filterbank.
  • Realized dynamic variations in filter magnitude response as a weighted sum of three fixed filters (high-, mid-, low-intensity).

Main Results:

  • The gammawarp filterbank demonstrated a substantial improvement in execution speed compared to previous dcGC implementations.
  • The gammawarp implementation was found to be 24 to 38 times faster than the original dcGC Matlab code.
  • Achieved identical phase responses for all filters within the filterbank due to symmetrical coefficient constraints.

Conclusions:

  • The gammawarp filterbank provides a computationally efficient alternative for implementing dcGC auditory filters.
  • This faster implementation can benefit applications predicting speech intelligibility and quality, especially those dealing with hearing loss.
  • The method allows for efficient dynamic adjustments of the filterbank's magnitude response.