The computational auditory signal processing and perception model: A revised version

Area of Science:

• Auditory Neuroscience
• Computational Auditory Modeling
• Psychoacoustics

Background:

• Existing computational auditory models often lack detailed representation of inner hair cell (IHC) transduction saturation.
• This limitation affects the accuracy of auditory perception simulations at high sound pressure levels.

Purpose of the Study:

• To integrate a non-linear IHC model into the Computational Auditory Signal Processing and Perception (CASP) model.
• To enhance the CASP model's ability to simulate auditory processing and perception, especially concerning non-linear effects.

Main Methods:

• Incorporation of a non-linear IHC transduction model into the existing CASP framework.
• Refinement of model parameters to accommodate the new non-linearity and improve usability.
• Validation against psychoacoustic data including intensity discrimination, masking, and modulation detection.

Main Results:

• The revised CASP model accurately predicts performance across various auditory tasks for normal-hearing listeners.
• The model effectively captures the impact of compressive non-linearity in the IHC transduction process.
• The updated model demonstrates improved predictive power and usability for auditory simulations.

Conclusions:

• The revised CASP model provides a more accurate and intuitive framework for simulating auditory perception.
• This enhanced model is valuable for investigating the role of non-linear auditory properties in internal representations.
• The model can be applied to study the effects of sensorineural hearing loss on auditory perception.