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Predicting the overall spatial quality of automotive audio systems.

Koya, Daisuke (2017) Predicting the overall spatial quality of automotive audio systems. Masters thesis, University of Surrey.

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Abstract

The spatial quality of automotive audio systems is often compromised due to their unideal listening environments. Automotive audio systems need to be developed quickly due to industry demands. A suitable perceptual model could evaluate the spatial quality of automotive audio systems with similar reliability to formal listening tests but take less time. Such a model is developed in this research project by adapting an existing model of spatial quality for automotive audio use. The requirements for the adaptation were investigated in a literature review. A perceptual model called QESTRAL was reviewed, which predicts the overall spatial quality of domestic multichannel audio systems. It was determined that automotive audio systems are likely to be impaired in terms of the spatial attributes that were not considered in developing the QESTRAL model, but metrics are available that might predict these attributes. To establish whether the QESTRAL model in its current form can accurately predict the overall spatial quality of automotive audio systems, MUSHRA listening tests using headphone auralisation with head tracking were conducted to collect results to be compared against predictions by the model. Based on guideline criteria, the model in its current form could not accurately predict the overall spatial quality of automotive audio systems. To improve prediction performance, the QESTRAL model was recalibrated and modified using existing metrics of the model, those that were proposed from the literature review, and newly developed metrics. The most important metrics for predicting the overall spatial quality of automotive audio systems included those that were interaural cross-correlation (IACC) based, relate to localisation of the frontal audio scene, and account for the perceived scene width in front of the listener. Modifying the model for automotive audio systems did not invalidate its use for domestic audio systems. The resulting model predicts the overall spatial quality of 2- and 5-channel automotive audio systems with a cross-validation performance of R^2 = 0.85 and root-mean-square error (RMSE) = 11.03%.

Item Type: Thesis (Masters)
Divisions : Theses
Authors :
NameEmailORCID
Koya, DaisukeUNSPECIFIEDUNSPECIFIED
Date : 30 November 2017
Funders : Bang & Olufsen
Contributors :
ContributionNameEmailORCID
http://www.loc.gov/loc.terms/relators/THSMason, RussellR.Mason@surrey.ac.ukUNSPECIFIED
http://www.loc.gov/loc.terms/relators/THSDewhirst, MartinUNSPECIFIEDUNSPECIFIED
http://www.loc.gov/loc.terms/relators/THSHummersone, Christopherc.hummersone@surrey.ac.ukUNSPECIFIED
Uncontrolled Keywords : spatial audio, automotive audio, perceptual modelling
Depositing User : Daisuke Koya
Date Deposited : 15 Dec 2017 11:08
Last Modified : 15 Dec 2017 11:08
URI: http://epubs.surrey.ac.uk/id/eprint/844659

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