AI 中文总结
本研究以大规模个性化空间音频的HRTF测量难题为背景，用Mesh2HRTF生成合成HRTF，实验证实其定位性能接近实测HRTF，虽存在数值与感知偏差的不一致，但可保留行为定位表现。
AI 中文摘要
大规模个性化空间音频仍面临大规模个体测量头相关传递函数（HRTF）的核心挑战，这促使人们对合成HRTF的兴趣日益浓厚。本研究使用Mesh2HRTF边界元法模拟生成合成HRTF，基于Extended SONICOM数据集，将其与实测HRTF及KEMAR HRTF在数值、计算和行为层面的有效性进行评估。在200名受试者中，合成HRTF在耳间时间差和耳间级差上与实测值的偏差小于KEMAR，但残留误差及升高的频谱失真集中在低后仰角处，这与合成流程中省略躯干几何结构的情况一致。两个计算模型显示出对应的预测定位误差模式，合成HRTF的表现介于实测HRTF和KEMAR之间。在虚拟现实定位任务（N=20）中，合成HRTF在所有极坐标指标上与实测HRTF匹配，而KEMAR的表现显著更差；不过无论实验条件如何，行为误差都集中在前后中线附近，并未出现在数值或模型所暗示的低仰角处。另一项空间掩蔽释放任务（N=18）显示HRTF类型无影响。综合结果表明，尽管合成HRTF存在数值/模型预测偏差与行为误差空间模式的不一致，但高分辨率合成HRTF仍能保留行为定位性能。
英文摘要
Individually measuring head-related transfer functions (HRTFs) at scale remains a central challenge for personalised spatial audio, motivating growing interest in synthetic HRTFs. We evaluated the numerical, computational, and behavioural validity of synthetic HRTFs, generated through the boundary element method simulation using Mesh2HRTF, against measured and KEMAR HRTFs using the Extended SONICOM dataset. Across 200 subjects, synthetic HRTFs deviated less from measured than KEMAR in interaural time and level differences, but residual errors, together with elevated spectral distortion, concentrated at low, rear elevations. This is consistent with the omission of torso geometry from the synthesis pipeline. Two computational models revealed a corresponding pattern of predicted localisation errors, with synthetic HRTFs positioned between measured and KEMAR. In a virtual reality localisation task (N = 20), synthetic HRTFs matched measured on every polar metric, while KEMAR was significantly worse. However, behavioural error clustered around the front-back midline regardless of condition, not at the low elevations implicated numerically or by the models. A separate spatial release from masking task (N = 18) showed no effect of HRTF type. Together, these results indicate that high-resolution synthetic HRTFs preserve behavioural localisation performance, despite discrepancies between the numerical/model-predicted bias and the spatial pattern of behavioural error.
CommentsVersion 2 clarifies in the pdf this is a preprint submitted to JASA and awaiting review
