Effect of perceptually irrelevant variance in head-related transfer functions on principal component analysis

The significant amount of variance in head-related transfer functions (HRTFs) resulting from source location and subject dependencies have led researchers to use principal components analysis (PCA) to approximate HRTFs with a small set of basis functions. PCA minimizes a mean-square error, and conse...

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Bibliographic Details
Published inThe Journal of the Acoustical Society of America Vol. 133; no. 1; pp. EL1 - EL6
Main Author Breebaart, Jeroen
Format Journal Article
LanguageEnglish
Published United States 01.01.2013
Subjects
Analysis of Variance
Cues
Head Movements
Humans
Linear Models
Models, Statistical
Principal Component Analysis
Sound Localization
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ISSN0001-4966
1520-8524
1520-9024
1520-8524
DOI10.1121/1.4769820

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Summary:The significant amount of variance in head-related transfer functions (HRTFs) resulting from source location and subject dependencies have led researchers to use principal components analysis (PCA) to approximate HRTFs with a small set of basis functions. PCA minimizes a mean-square error, and consequently may spend modeling effort on perceptually irrelevant properties. To investigate the extent of this effect, PCA performance was studied before and after removal of perceptually irrelevant variance. The results indicate that from the sixth PCA component onward, a substantial amount of perceptually irrelevant variance is being accounted for.
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ISSN:0001-4966
1520-8524
1520-9024
1520-8524
DOI:10.1121/1.4769820