The effect of compression on tuning estimates in a simple nonlinear auditory filter model | Zendy

Márton Marschall | Zendy; Ewen MacDonald | Zendy; Torsten Dau | Zendy

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The effect of compression on tuning estimates in a simple nonlinear auditory filter model

Author(s) -

Márton Marschall,

Ewen MacDonald,

Torsten Dau

Publication year - 2013

Publication title -

proceedings of meetings on acoustics

Language(s) - English

Resource type - Conference proceedings

ISSN - 1939-800X

DOI - 10.1121/1.4799637

Subject(s) - basilar membrane , nonlinear system , gas compressor , filter (signal processing) , masking (illustration) , computer science , band pass filter , control theory (sociology) , compression (physics) , frequency response , acoustics , speech recognition , engineering , electronic engineering , physics , cochlea , artificial intelligence , medicine , art , control (management) , electrical engineering , quantum mechanics , visual arts , computer vision , anatomy , thermodynamics , mechanical engineering

Behavioral experiments using auditory masking have been used to characterize frequency selectivity, one of the basic properties of the auditory system. However, due to the nonlinear response of the basilar membrane, the interpretation of these experiments may not be straightforward. Specifically, there is evidence that human frequency-selectivity estimates depend on whether an iso-input or an iso-response measurement paradigm is used (Eustaquio-Martin et al., 2011). This study presents simulated tuning estimates using a simple compressive auditory filter model, the bandpass nonlinearity (BPNL), which consists of a compressor between two bandpass filters. The BPNL forms the basis of the dual-resonance nonlinear (DRNL) filter that has been used in a number of modeling studies. The location of the nonlinear element and its effect on estimated tuning in the two measurement paradigms was investigated. The results show that compression leads to (i) a narrower tuning estimate in the iso-response paradigm when a ...

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