Localization in Elevation with Non-Individual Head-Related Transfer Functions: Comparing Predictions of Two Auditory Models

Roberto Barumerli, Michele Geronazzo, Federico Avanzini

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

5 Citations (Scopus)

Abstract

This paper explores the limits of human localization of sound sources when listening with non-individual Head-Related Transfer Functions (HRTFs), by simulating performances of a localization task in the mid-sagittal plane. Computational simulations are performed with the CIPIC HRTF database using two different auditory models which mimic human hearing processing from a functional point of view. Our methodology investigates the opportunity of using virtual experiments instead of time- and resource- demanding psychoacoustic tests, which could also lead to potentially unreliable results. Four different perceptual metrics were implemented in order to identify relevant differences between auditory models in a selection problem of best-available non-individual HRTFs. Results report a high correlation between the two models denoting an overall similar trend, however, we discuss discrepancies in the predictions which should be carefully considered for the applicability of our methodology to the HRTF selection problem.
Original languageEnglish
Title of host publicationProceedings of 26th European Signal Processing Conference (EUSIPCO 2018)
Number of pages5
PublisherIEEE
Publication dateSept 2018
Article number8553320
ISBN (Print)978-1-5386-3736-4, 978-90-827970-0-8
ISBN (Electronic)978-9-0827-9701-5
DOIs
Publication statusPublished - Sept 2018
Event26th European Signal Processing Conference (EUSIPCO 2018) - Rome, Italy
Duration: 3 Sept 20187 Sept 2018
Conference number: 26
http://www.eusipco2018.org

Conference

Conference26th European Signal Processing Conference (EUSIPCO 2018)
Number26
Country/TerritoryItaly
CityRome
Period03/09/201807/09/2018
Internet address
SeriesProceedings of the European Signal Processing Conference
ISSN2076-1465

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