Simulating the precedence effect by means of autocorrelation.

Abstract

A number of algorithms have been developed to simulate the robust localization performance of humans in reverberant conditions, the most successful of which are based on (contralateral) inhibition. While these models can demonstrate the precedence effect in general, their nonlinear behavior makes it difficult to optimize their settings. A linear algorithm has now been developed to overcome this limitation. An autocorrelation algorithm determines the delay between lead and lag and their amplitude ratio for both channels. An inverse filter is then used to eliminate the lag signal before it is localized with a standard localization algorithm. Interestingly, the filter contains both inhibitory and excitatory elements, and the filter’s impulse response looks somewhat similar to the response of a chopper cell. The algorithm operates robustly on top of a model of the auditory periphery (gammatone filterbank and halfwave rectification). Due to its linear nature, the model performs better if the full waveform is reconstructed by subtracting a delayed version of the halfwave‐rectified signal, with a delay time that corresponds to half the period of each frequency band’s center frequency. The model is able to simulate a number of experiments with ongoing stimuli and performs robustly with onset‐truncated and interaural‐level‐difference based stimuli.