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G. Mendonça, P. Dias, J. Vieira, J. Ferreira, "On the Improvement of Auditory Accuracy with Non-Indivisualized HRTF-Based Sounds," Paper 8266, (2010 November.). doi: G. Mendonça, P. Dias, J. Vieira, J. Ferreira, "On the Improvement of Auditory Accuracy with Non-Indivisualized HRTF-Based Sounds," Paper 8266, (2010 November.). doi:
Abstract: Auralization is a powerful tool to increase the realism and sense of immersion in Virtual Reality environments. The Head Related Transfer Function (HRTF) filters commonly used for auralization are non-individualized, as obtaining individualized HRTFs poses very serious practical difficulties. It is therefore extremely important to understand to what extent this hinders sound perception. In this paper, we address this issue from a learning perspective. In a set of experiments, we observed that mere exposure to virtual sounds processed with generic HRTF did not improve the subjects’ performance in sound source localization, but short training periods involving active learning and feedback led to significantly better results. We propose that using auralization with non-individualized HRTF should always be preceded by a learning period.

@article{mendonça2010on,
author={mendonça, catarina, santos, jorge, campos, guilherme and dias, paulo and vieira, josé and ferreira, joão},
journal={journal of the audio engineering society},
title={on the improvement of auditory accuracy with non-indivisualized hrtf-based sounds},
year={2010},
volume={},
number={},
pages={},
doi={},
month={november},} @article{mendonça2010on,
author={mendonça, catarina, santos, jorge, campos, guilherme and dias, paulo and vieira, josé and ferreira, joão},
journal={journal of the audio engineering society},
title={on the improvement of auditory accuracy with non-indivisualized hrtf-based sounds},
year={2010},
volume={},
number={},
pages={},
doi={},
month={november},
abstract={auralization is a powerful tool to increase the realism and sense of immersion in virtual reality environments. the head related transfer function (hrtf) filters commonly used for auralization are non-individualized, as obtaining individualized hrtfs poses very serious practical difficulties. it is therefore extremely important to understand to what extent this hinders sound perception. in this paper, we address this issue from a learning perspective. in a set of experiments, we observed that mere exposure to virtual sounds processed with generic hrtf did not improve the subjects’ performance in sound source localization, but short training periods involving active learning and feedback led to significantly better results. we propose that using auralization with non-individualized hrtf should always be preceded by a learning period.},}

TY - paper
TI - On the Improvement of Auditory Accuracy with Non-Indivisualized HRTF-Based Sounds
SP - EP -
AU - Mendonça, Catarina, Santos, Jorge, Campos, Guilherme
AU - Dias, Paulo
AU - Vieira, José
AU - Ferreira, João
PY - 2010
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - November 2010 TY - paper
TI - On the Improvement of Auditory Accuracy with Non-Indivisualized HRTF-Based Sounds
SP - EP -
AU - Mendonça, Catarina, Santos, Jorge, Campos, Guilherme
AU - Dias, Paulo
AU - Vieira, José
AU - Ferreira, João
PY - 2010
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - November 2010
AB - Auralization is a powerful tool to increase the realism and sense of immersion in Virtual Reality environments. The Head Related Transfer Function (HRTF) filters commonly used for auralization are non-individualized, as obtaining individualized HRTFs poses very serious practical difficulties. It is therefore extremely important to understand to what extent this hinders sound perception. In this paper, we address this issue from a learning perspective. In a set of experiments, we observed that mere exposure to virtual sounds processed with generic HRTF did not improve the subjects’ performance in sound source localization, but short training periods involving active learning and feedback led to significantly better results. We propose that using auralization with non-individualized HRTF should always be preceded by a learning period.