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Binaural rendering is typically assessed via timbre and localization accuracy, while its intrinsic spatial resolution remains rarely quantified. This paper proposes a perceptual evaluation method based on Minimum Audible Angle (MAA) measurements to estimate the azimuthal just-noticeable difference (JND) introduced by binaural rendering algorithms. We systematically compared several rendering algorithms across eight reference azimuths using two participant-allocation paradigms. The results show that spatial resolution is significantly influenced
by Ambisonic order and choice of the rendering algorithm, with MAA thresholds systematically decreasing as the truncation order increases. Furthermore, the proposed method successfully captures physiological spatial characteristics and identifies resolution limits imposed by reference angles. While both participant-allocation paradigms yield consistent qualitative trends, the repeated-measures design provides superior data stability. These findings demonstrate that the proposed MAA-based method is an effective tool for quantifying the spatial resolution
of binaural rendering algorithms.
Author (s): Qian, Yufan;
Zhu, Houlin;
Wu, Xihong;
Qu, Tianshu;
Affiliation:
State Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology, Peking University
(See document for exact affiliation information.)
AES Convention: 160
Paper Number:10292
Publication Date:
2026-05-28
Session subject:
Immersive Audio, Perception
DOI:
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Qian, Yufan; Zhu, Houlin; Wu, Xihong; Qu, Tianshu; 2026; A Perceptual Evaluation Method for Binaural Rendering Algorithms via Minimum Audible Angle Measurements [PDF]; State Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology, Peking University; Paper 10292; Available from: https://aes.org/publications/elibrary-page/?id=23189
Qian, Yufan; Zhu, Houlin; Wu, Xihong; Qu, Tianshu; A Perceptual Evaluation Method for Binaural Rendering Algorithms via Minimum Audible Angle Measurements [PDF]; State Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology, Peking University; Paper 10292; 2026 Available: https://aes.org/publications/elibrary-page/?id=23189
@inproceedings{Qian2026a,
title={{A Perceptual Evaluation Method for Binaural Rendering Algorithms via Minimum Audible Angle Measurements}},
author={Qian, Yufan and Zhu, Houlin and Wu, Xihong and Qu, Tianshu},
year={2026},
month={jun},
booktitle={Journal of the Audio Engineering Society},
publisher={},
number={10292},
organization={AES},
}
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