Abstract: There is provided a unique signal processing technique for localizing and characterizing each of a number of differently located acoustic sources. Specifically there is provided a method for auditory segregation of multiple voice inputs comprising the steps of: receiving a plurality of voice input signals from different source locations; filtering said voice input signals with head related transfer functions (HRTF) using a digital signal processor (DSP) thereby assigning the voice input signals to different locations in virtual auditory space; and changing the HRTF filtered voice input signals in two dimensions, wherein pitch is changed and the signal is filtered with different filters emulating vocal tracts of different sizes thereby further segregating the voice input signals from each other.

Abstract: There is provided a biomimetic robot modelling the highly directional lizard ear. Since the directionality is very robust, the neural processing is very simple. This mobile sound localizing robot can therefore easily be miniaturized. The invention is based on a simple electric circuit emulating the lizard ear acoustics with sound input from two small microphones. The circuit generates a robust directionality around 2-4 kHz. The output of the circuit is fed to a model nervous system. The nervous system model is bilateral and contains a set of band-pass filters followed by simulated EI-neurons that compare inputs from the two ears. This model is implemented in software on a digital signal processor and controls the left and right-steering motors of the robot. Additionally, the nervous system model contains a neural network that can self-adapt so as to auto-calibrate the device.