8–12 Sept 2026
Europe/Vienna timezone

Nonlinear Harmonic Prediction and Compensation in HRTF Measurements

FA2026/867
9 Sept 2026, 16:40
20m
Saal 4 (Messe Congress Graz)

Saal 4

Messe Congress Graz

A24 Virtual Acoustics A24.00 HRTF processing and modeling

Speaker

Payman Azaripasand (Technical University of Munich)

Description

The exponential sine sweep (ESS) technique became the common approach for measuring head-related transfer functions (HRTFs) since it allows separating the loudspeaker’s distortion from the HRTF by temporal windowing. This, however, fails with overlapping excitation signals. This work assesses the signal-to-noise ratio (SNR) benefit from nonlinear harmonic prediction and subtraction. The measured response is modeled as a superposition of a linear response, nonlinear harmonic distortions, and additive noise. Each harmonic distortion component is represented using a finite impulse response kernel. The kernel is estimated from a reference measurement. For evaluation, broadband and Bark-band limited SNR is computed. Preliminary results for frontal HRTF measurements show broadband SNR values of 30-45 dB depending on the loudspeaker direction, with the proposed harmonic subtraction improving these values by up to about 3 dB for the most affected (most elevated) channel. In perceptually relevant mid-to-high frequency regions, where spectral notches make the HRTF sensitive to measurement noise, mean SNR gains of 1-2 dB are observed. The results demonstrate that the proposed method has potential to reduce non-linear distortion and provide cleaner impulse responses and more accurate noise estimates in overlapping ESS-based HRTF measurements.

Authors

Payman Azaripasand (Technical University of Munich) Bernhard U. Seeber (Technische Universität München)

Presentation materials