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Acquisition of Continuous-Distance Near-Field Head-Related Transfer Functions on KEMAR Using Adaptive Filtering

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Near-field Head-Related Transfer Functions (HRTFs) depend on both source direction (azimuth/elevation) and distance. The acquisition procedure for near-field HRTF data on a dense spatial grid is time-consuming and prone to measurement errors. Therefore, existing databases only cover a few discrete source distances. Coming from the fact that continuous-azimuth acquisition of HRTFs has been made possible by applying the Normalized Least Mean Square (NLMS) adaptive filtering method, in this work we applied the NLMS algorithm in measuring near-field HRTFs under continuous variation of source distance. We developed and validated a novel measurement setup that allows the acquisition of near-field HRTFs for source distances ranging from 20 to 120 cm with one recording. We then evaluated the measurement accuracy by analyzing the estimation error from the adaptive filtering algorithm and the key characteristics of the measured HRTFs associated with near-field binaural rendering.

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Permalink: https://www.aes.org/e-lib/browse.cfm?elib=21688


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