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A. Andreopoulou, and BR. G.. Katz, "Perceptual Impact on Localization Quality Evaluations of Common Pre-Processing for Non-Individual Head-Related Transfer Functions," J. Audio Eng. Soc., vol. 70, no. 5, pp. 340-354, (2022 May.). doi: https://doi.org/10.17743/jaes.2022.0008 A. Andreopoulou, and BR. G.. Katz, "Perceptual Impact on Localization Quality Evaluations of Common Pre-Processing for Non-Individual Head-Related Transfer Functions," J. Audio Eng. Soc., vol. 70 Issue 5 pp. 340-354, (2022 May.). doi: https://doi.org/10.17743/jaes.2022.0008
Abstract: This article investigates the impact of two commonly used Head-Related Transfer Function (HRTF) processing/modeling methods on the perceived spatial accuracy of binaural data by monitoring changes in user ratings of non-individualized HRTFs. The evaluated techniques are minimum-phase approximation and Infinite-Impulse Response (IIR) modeling. The study is based on the hypothesis that user-assessments should remain roughly unchanged, as long as the range of signal variations between processed and unprocessed (reference) HRTFs lies within ranges previously reported as perceptually insignificant. Objective assessments of the degree of spectral variations between reference and processed data, computed using the Spectral Distortion metric, showed no evident perceptually relevant variations in the minimum-phase data and spectral differences marginally exceeding the established thresholds for the IIR data, implying perceptual equivalence of spatial impression in the tested corpus. Nevertheless analysis of user responses in the perceptual study strongly indicated that variations introduced in the data by the tested methods of HRTF processing can lead to inversions in quality assessment, resulting in the perceptual rejection of HRTFs that were previously characterized in the ratings as the "most appropriate" or alternatively in the preference of datasets that were previously dismissed as "unfit." The effect appears more apparent for IIR processing and is equally evident across the evaluated horizontal and median planes.

@article{andreopoulou2022perceptual,
author={andreopoulou, areti and katz, brian f. g.},
journal={journal of the audio engineering society},
title={perceptual impact on localization quality evaluations of common pre-processing for non-individual head-related transfer functions},
year={2022},
volume={70},
number={5},
pages={340-354},
doi={https://doi.org/10.17743/jaes.2022.0008},
month={may},} @article{andreopoulou2022perceptual,
author={andreopoulou, areti and katz, brian f. g.},
journal={journal of the audio engineering society},
title={perceptual impact on localization quality evaluations of common pre-processing for non-individual head-related transfer functions},
year={2022},
volume={70},
number={5},
pages={340-354},
doi={https://doi.org/10.17743/jaes.2022.0008},
month={may},
abstract={this article investigates the impact of two commonly used head-related transfer function (hrtf) processing/modeling methods on the perceived spatial accuracy of binaural data by monitoring changes in user ratings of non-individualized hrtfs. the evaluated techniques are minimum-phase approximation and infinite-impulse response (iir) modeling. the study is based on the hypothesis that user-assessments should remain roughly unchanged, as long as the range of signal variations between processed and unprocessed (reference) hrtfs lies within ranges previously reported as perceptually insignificant. objective assessments of the degree of spectral variations between reference and processed data, computed using the spectral distortion metric, showed no evident perceptually relevant variations in the minimum-phase data and spectral differences marginally exceeding the established thresholds for the iir data, implying perceptual equivalence of spatial impression in the tested corpus. nevertheless analysis of user responses in the perceptual study strongly indicated that variations introduced in the data by the tested methods of hrtf processing can lead to inversions in quality assessment, resulting in the perceptual rejection of hrtfs that were previously characterized in the ratings as the "most appropriate" or alternatively in the preference of datasets that were previously dismissed as "unfit." the effect appears more apparent for iir processing and is equally evident across the evaluated horizontal and median planes.},}

TY - paper
TI - Perceptual Impact on Localization Quality Evaluations of Common Pre-Processing for Non-Individual Head-Related Transfer Functions
SP - 340 EP - 354
AU - Andreopoulou, Areti
AU - Katz, Brian F. G.
PY - 2022
JO - Journal of the Audio Engineering Society
IS - 5
VO - 70
VL - 70
Y1 - May 2022 TY - paper
TI - Perceptual Impact on Localization Quality Evaluations of Common Pre-Processing for Non-Individual Head-Related Transfer Functions
SP - 340 EP - 354
AU - Andreopoulou, Areti
AU - Katz, Brian F. G.
PY - 2022
JO - Journal of the Audio Engineering Society
IS - 5
VO - 70
VL - 70
Y1 - May 2022
AB - This article investigates the impact of two commonly used Head-Related Transfer Function (HRTF) processing/modeling methods on the perceived spatial accuracy of binaural data by monitoring changes in user ratings of non-individualized HRTFs. The evaluated techniques are minimum-phase approximation and Infinite-Impulse Response (IIR) modeling. The study is based on the hypothesis that user-assessments should remain roughly unchanged, as long as the range of signal variations between processed and unprocessed (reference) HRTFs lies within ranges previously reported as perceptually insignificant. Objective assessments of the degree of spectral variations between reference and processed data, computed using the Spectral Distortion metric, showed no evident perceptually relevant variations in the minimum-phase data and spectral differences marginally exceeding the established thresholds for the IIR data, implying perceptual equivalence of spatial impression in the tested corpus. Nevertheless analysis of user responses in the perceptual study strongly indicated that variations introduced in the data by the tested methods of HRTF processing can lead to inversions in quality assessment, resulting in the perceptual rejection of HRTFs that were previously characterized in the ratings as the "most appropriate" or alternatively in the preference of datasets that were previously dismissed as "unfit." The effect appears more apparent for IIR processing and is equally evident across the evaluated horizontal and median planes.