Enhanced Individualization of Head-Related Impulse Response Model in Horizontal Plane Based on Multiple Regression Analysis

Hugeng, Hugeng; Wahab, Wahidin; Gunawan, Dadang

doi:10.1109/iccea.2010.197

Cited by 4 publications

(11 citation statements)

References 7 publications

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“…Applying the HRIRs mp of 35 subjects for sources on the horizontal plane, individualization using MLR between the chosen parameters and PCWs, w i (θ), provides the average error of 22.22 %. This result is close to when we employed data from 37 subjects, that is 22.50% [13]. Here we came to the opinion that our selection method of anthropometric parameters before as in [13] is fully confirmed with the selection method explained in this paper.…”

Section: Experiments' Results and Discussionsupporting

confidence: 86%

“…Observing the anthropometries database, there are many parameters, namely x 4 , x 5 , x 13 , d 8 , θ 1 , and θ 2 that could not be simply measured because of the difficulty in determining the reference points and the parameters are so small (only several millimeters) that one needs a very precise instruments. These 6 parameters also have weak correlations with maximum ITD (ITD max ).…”

Section: Experiments' Results and Discussionmentioning

confidence: 99%

“…x 1 , x 3 , x 6 , x 12 , d 1 , d 3 , d 5 , and d 6 , which were explained before in [13]. Correlation analysis is applied to determine parameters that have strong correlation with ITD max .…”

Section: Experiments' Results and Discussionmentioning

confidence: 99%

“…Correlation analysis is used to select the independent variables in obtaining more accurate and simpler MLR model, as explained in [13].…”

Section: Multiple Linear Regression Modelingmentioning

confidence: 99%

“…The individualization of HRIRs mp for sound sources on the horizontal plane was explained and investigated in [13] that used the same individualization method as one that is explained in this paper. In [14], individualization of magnitude HRTFs for sound sources on horizontal plane was investigated.…”

Section: Introductionmentioning

confidence: 99%

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A New Selection Method of Anthropometric Parameters in Individualizing HRIR

Hugeng¹,

Wahab

Gunawan

2015

TELKOMNIKA

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Section: Experiments' Results and Discussionsupporting

confidence: 86%

Section: Experiments' Results and Discussionmentioning

confidence: 99%

Section: Experiments' Results and Discussionmentioning

confidence: 99%

“…Correlation analysis is used to select the independent variables in obtaining more accurate and simpler MLR model, as explained in [13].…”

Section: Multiple Linear Regression Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A New Selection Method of Anthropometric Parameters in Individualizing HRIR

Hugeng¹,

Wahab

Gunawan

2015

TELKOMNIKA

Self Cite

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Magnitude Modelling of HRTF Using Principal Component Analysis Applied to Complex Values

Ramos¹,

Tommasini²

2015

Archives of Acoustics

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Principal components analysis (PCA) is frequently used for modelling the magnitude of the headrelated transfer functions (HRTFs). Assuming that the HRTFs are minimum phase systems, the phase is obtained from the Hilbert transform of the log-magnitude. In recent years, the PCA applied to HRTFs is also used to model individual HRTFs relating the PCA weights with anthropometric measurements of the head, torso and pinnae. The HRTF log-magnitude is the most used format of input data to the PCA, but it has been shown that if the input data is HRTF linear magnitude, the cumulative variance converges faster, and the mean square error (MSE) is smaller. This study demonstrates that PCA applied directly on HRTF complex values is even better than the two formats mentioned above, that is, the MSE is the smallest and the cumulative variance converges faster after the 8th principal component. Different objective experiments around all the median plane put in evidence the differences which, although small, seem to be perceptually detectable. To elucidate this point, psychoacoustic discrimination tests are done between measured and reconstructed HRTFs from the three types of input data mentioned, in the median plane between −45• and +90• .

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