Towards the Neuromorphic Implementation of the Auditory Perception in the iCub Robotic Platform

Abstract

Hearing can be considered as one of the most important senses since it plays a key role in the audiovisual learning process. While a lot of effort has been made for achieving good results from the traditional approach of auditory perception, new trends such as neuromorphic computing are showing promising achievements in the implementation of brain structures for sensory perception. In this work, the design and integration of a neuromorphic event-based digital model of the auditory ascending pathway within the iCub robotic platform is proposed. This model, which comprises from the cochlea up to the inferior colliculus, replaces the traditional approach for sound processing already implemented on iCub and is able to perform sound recognition and spatial localization in real-time, allowing the implementation of auditory attention models in complex scenarios, like the cocktail party problem.