Auptimize：面向扩展现实的空间音频线索最优布局
Auptimize: Optimal Placement of Spatial Audio Cues for Extended Reality
AI总结：
针对扩展现实中人类听觉感知局限导致的空间音频声源定位误差问题，提出利用腹语效应的Auptimize方法，通过解耦视声位置优化声源布局，降低识别错误率，适用于多种交互式XR场景。
摘要：
扩展现实（XR）中的空间音频能让用户更好地感知虚拟元素的放置位置，还能高效引导用户关注各类事件，比如通知、不同窗口的系统警报，或是正在靠近的虚拟化身。但由于人类听觉感知存在角度辨别误差、前后混淆等局限性，人类对声音线索的定位并不准确，在存在多个声源时尤其如此。这会降低XR界面的效率，因为用户会误判声音来自哪个XR元素。为解决这一问题，我们提出了Auptimize——一种用于XR声源布局的新型计算方法，它利用腹语效应来缓解这类定位误差。Auptimize将声源位置与视觉元素解耦，把声源重新定位到最优位置，以实现声音线索的清晰识别，避免因声源距离过近和前后混淆产生的误差。我们的评估显示，与在配对的视声位置播放声音线索相比，Auptimize降低了基于空间音频的声源识别错误率。我们还验证了Auptimize适用于多种基于空间音频的交互式XR场景。
英文摘要：
Spatial audio in Extended Reality (XR) provides users with better awareness of where virtual elements are placed, and efficiently guides them to events such as notifications, system alerts from different windows, or approaching avatars. Humans, however, are inaccurate in localizing sound cues, especially with multiple sources due to limitations in human auditory perception such as angular discrimination error and front-back confusion. This decreases the efficiency of XR interfaces because users misidentify from which XR element a sound is coming. To address this, we propose Auptimize, a novel computational approach for placing XR sound sources, which mitigates such localization errors by utilizing the ventriloquist effect. Auptimize disentangles the sound source locations from the visual elements and relocates the sound sources to optimal positions for unambiguous identification of sound cues, avoiding errors due to inter-source proximity and front-back confusion. Our evaluation shows that Auptimize decreases spatial audio-based source identification errors compared to playing sound cues at the paired visual-sound locations. We demonstrate the applicability of Auptimize for diverse spatial audio-based interactive XR scenarios.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
