Computational models for predicting sound quality

Abstract

The quality of an audio device, such as a microphone, amplifier, or headphone, depends on how accurately the device transmits the properties of the sound source to the ear(s) of the listener. Two types of “distortion” can occur in this transmission: (1) “Linear” distortion, which may be described as a deviation of the frequency response from the “target” response; (2) Nonlinear distortion, which is characterised by frequency components in the output of the device that were not present in the input. These two forms of distortion have different perceptual effects. Their effects on sound quality can be predicted using a model of auditory processing with the following stages: (1) A filter to take into account the transmission of sound from the device to the ear of the listener; (2) A filter to simulate the effects of transmission through the middle ear; (3) An array of bandpass filters to simulate the auditory filters that exist in the cochlea of the inner ear. For predicting the perceptual effects of linear distortion, a model operating in the frequency domain can be used. For predicting the perceptual effects of nonlinear distortion, a model operating in the time domain is required, since the detailed waveforms at the outputs of the auditory filters need to be considered. The models described have been shown to give accurate predictions for a wide range of “artificial” and “real” linear and nonlinear distortions.