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A controlled listening test was conducted on 31 different models of around-ear (AE) and on-ear (OE) headphones to determine listeners’ sound quality preferences. One-hundred-thirty listeners both trained and untrained rated the headphones based on preference using a virtual headphone method that used a single replicator headphone equalized to match magnitude and minimum phase responses of the different headphones. Listeners rated seven different headphones in each trial that included high (the new Harman AE-OE target curve) and low anchors. On average, both trained and untrained listeners preferred the high anchor to 31 other choices. Using machine learning a model was developed that predicts the listeners’ headphone preference ratings of the headphones based on deviation in magnitude response from the Harman target curve.
Author (s): Olive, Sean; Welti, Todd; Khonsaripour, Omid
Affiliation:
Harman International, Northridge, CA, USA
(See document for exact affiliation information.)
AES Convention: 144
Paper Number:9919
Publication Date:
2018-05-06
Import into BibTeX
Session subject:
Audio Quality Part 1
Permalink: https://aes2.org/publications/elibrary-page/?id=19436
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Olive, Sean; Welti, Todd; Khonsaripour, Omid; 2018; A Statistical Model that Predicts Listeners’ Preference Ratings of Around-Ear and On-Ear Headphones [PDF]; Harman International, Northridge, CA, USA; Paper 9919; Available from: https://aes2.org/publications/elibrary-page/?id=19436
Olive, Sean; Welti, Todd; Khonsaripour, Omid; A Statistical Model that Predicts Listeners’ Preference Ratings of Around-Ear and On-Ear Headphones [PDF]; Harman International, Northridge, CA, USA; Paper 9919; 2018 Available: https://aes2.org/publications/elibrary-page/?id=19436