Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/26405

TitleOn the improvement of localization accuracy with nonindividualized HRTF-based sounds
Author(s)Mendonça, Catarina
Campos, Guilherme
Dias, Paulo
Vieira, José
Ferreira, João P.
Santos, Jorge A.
Issue date26-Nov-2012
PublisherAudio Engineering Society
JournalJournal of the Audio Engineering Society
CitationMendonça, C., Campos, G., Dias, P., Vieira, J., Ferreira, J. P., & Santos, J. A. (2012). On the Improvement of Localization Accuracy with Non-Individualized HRTF-Based Sounds. Journal of the Audio Engineering Society, 60(10), 821-830.
Abstract(s)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.
TypeArticle
URIhttp://hdl.handle.net/1822/26405
ISSN1549-4950
Publisher versionhttps://secure.aes.org/forum/pubs/journal/?elib=16555
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CAlg - Artigos em revistas internacionais/Papers in international journals
CIPsi - Artigos (Papers)

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