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• W202294182 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) to be known in every point of the 3D space and for each subject. These functions can be determined by using a quite complex procedure, which requires many measurements for each individual. In the present paper, an updated version of the previously proposed artificial neural network (ANN) is presented and used, in order to generate the HRTFs. The proposed method, valid for any 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." @default.
• W202294182 created "2016-06-24" @default.
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• W202294182 date "2010-07-22" @default.
• W202294182 modified "2023-09-26" @default.
• W202294182 title "Multi-subject head related transfer function generation using artificial neural networks" @default.
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