Generation of the head related transfer functions using artificial neural networks

  • Authors:
  • Zoltan Haraszy;Daniel Ianchis;Virgil Tiponut

  • Affiliations:
  • Department of Applied Electronics, POLITEHNICA University of Timisoara, Timisoara, Romania;Department of Applied Electronics, POLITEHNICA University of Timisoara, Timisoara, Romania;Department of Applied Electronics, POLITEHNICA University of Timisoara, Timisoara, Romania

  • Venue:
  • ICC'09 Proceedings of the 13th WSEAS international conference on Circuits
  • Year:
  • 2009

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Abstract

The new Acoustic Virtual Reality (AVR) concept is often used as a man-machine interface in electronic travel aid (ETA), that help blind and visually impaired individuals to navigate in real outdoor environments. According to this concept, the presence of obstacles in the surrounding environment and the path to the desired target will be signalized to the blind subject by burst of sounds, whose virtual source position suggests the position of the real obstacles and the direction of movement, respectively. The practical implementation of the AVR concept requires the so-called Head Related Transfer Functions (HRTFs) values to be known in every point of the 3D space and for each subject. These values can be determined by using a quite complex procedure, which requires many measurements for each individual. In the present paper, an artificial neural network (ANN) is proposed in order to generate the values of the HRTFs. The proposed method, valid for only on subject, speeds up the implementation of the AVR concept after the ANN training has been completed. Finally, some experimental results, conclusions and further developments are also presented.