Binaural sound localization in an artificial neural network

Binaural Sound Localization in Spiking Neural Networks

Estimating the azimuth of a sound source from the binaural spectral amplitude

A computational model of auditory localization based on processing spectral amplitude cues for localizing broadband high frequency sound sources is presented. The cues extracted are binaural spectral level di erence patterns of the Head Related Transfer Functions (HRTF) corresponding to the direction of the sound source. Four di erent pattern classi ers are used to evaluate the feasibility of l...

Design and Implementation of a Hierarchical Robotic System: A Platform for Artificial Intelligence Investigation

Robots need to act in the real world, but they are constrained by weight, power, and computation capability. Artificial intelligence (AI) techniques try to mimic the clever processing of living creatures, but they lack embodiment and a realistic environment. This thesis introduces a novel robotic architecture that provides slender robots with massive processing and parallel computation potentia...

A report on sound event detection with different binaural features

In this paper, we compare the performance of using binaural audio features in place of single channel features for sound event detection. Three different binaural features are studied and evaluated on the publicly available TUT Sound Events 2017 dataset of length 70 minutes. Sound event detection is performed separately with single channel and binaural features using stacked convolutional and r...

A Spike-Based Model of Binaural Sound Localization

This paper describes a spike-based model of binaural sound localization using interaural time differences (ITDs). To handle the problem of temporal coding and to facilitate a hardware implementation all neurons are simulated by a spike response model, which includes postsynaptic potentials (PSPs) and a refractory period. A winner-take-all (WTA) network selects the dominant source from the repre...