3D Sound applied to the design of Assisted Navigation Devices for the Visually Impaired

Abstract

This work presents an approach to generate 3D sound by using a set of artificial neural networks (ANNs). The proposed method is capable to reconstruct the Head Related Impulse Responses (HRIRs) by means of spatial interpolation. In order to cover the whole reception auditory space, without increasing the network complexity, a structure of multiple networks (set), each one modeling a specific area was adopted. The three main factors that influence the model accuracy --- the network's architecture, the reception area's aperture angles and the HRIR's time shifts --- are investigated and an optimal setup is presented. The computational effort to process the ANN is shown to be slightly smaller than traditional interpolation methods and all error calculation reached very low levels, validating the method to be used in the design of a 3D sound emitter capable of provide navigation aid for the visually impaired. Two approaches are presented in order to detect obstacles, one which makes use of computational vision techniques and other with laser proximity sensors.

Keywords

• Acoustical Virtual Reality
• Auralization
• Artificial Neural Networks
• HRIR Interpolation
• ETA devices