Efficient Algorithm for Extracting Essential Head Related Impulse Response Data for Acoustic Virtual Reality Development

摘要

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) to be known in every point of the 3D space and for each involved individual. In the present paper, we describe an efficient algorithm for extracting essential Head Related Impulse Response (HRIR) data, we apply it for one person's HRIRs from the Listen Ircam HRTF database. To verify its applicability, after describing the experimental setup, listening tests are also conducted and results are compared with the results of listening tests without using the proposed algorithm. Finally, conclusions and future research ideas are also presented.