Sound in Space: towards a unified theory of auditory localization

空间声音：迈向听觉定位的统一理论

• 批准号: RGPIN-2019-06121
• 负责人: Guastavino, Catherine
• 金额: $ 4.01万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=715939
• 关键词: Sound; Space; towards; unified; theory

One of the major challenges to the auditory system is to track sound sources as they move to predict their future path and guide action (e.g. avoid an approaching car). Yet, dynamic sound localization, our ability to determine the position of sounds as they move in space, has largely been understudied due to the complications of laboratory setups. The long-term goal of this program is to understand the perceptual and cognitive underpinnings of auditory motion in an attempt to reconcile current theories of static and dynamic sound localization. Our recent work has demonstrated the existence of upper limits of auditory motion in a range of velocities that had not been explored before. Based on this work, we hypothesize that auditory motion is based on the comparison of static localization cues at successive points in time, constrained by the temporal resolution of the binaural system (blurred snapshot model). But our work so far focused on azimuthal localization using sounds revolving at a fixed distance on the horizontal plane. To test our hypothesis and the relative contributions of different localization cues, we will extend our investigation to trajectories resulting in changes in intensity, direct to reverberant ratio and Doppler shifts. To do so, we first need to characterize spatial audio rendering techniques in terms of their ability to preserve localization cues at the listeners' ears. We will then systematically investigate the effect on monaural and binaural localization cues on motion perception. In later years, we will examine the effect of spatial features on grouping processes of dynamic sound sources in complex auditory scenes with multiple simultaneous trajectories. In parallel, we will implement models of sound localization informed by the results of experiments with human listeners. We will proceed by a progressive complexification, starting with a simple model of azimuthal localization of sounds at a fixed distance, then adding motion-induced blur, then modeling distance and velocity estimation, and finally accounting for our ability to track multiple sounds sources simultaneously. In Year 5, we will integrate the different cues in a Bayesian observer model for optimal prediction, similar to the ones used for visual motion perception. The predictions will be compared with empirical findings to test alternative theories of sound localization. On theoretical grounds, this research program will provide grounds for a unified theory of sound localization. This program has practical implications for spatial sound reproduction (in virtual reality, entertainment, videoconferencing), for improving spatial functionalities in hearing aids and for acoustic monitoring of target sounds. Future directions include multisensory integration in motion perception by investigating how the visual and auditory system can provide complementary information about the movement of objects.

听觉系统面临的主要挑战之一是在声源移动时跟踪声源，以预测其未来路径并指导行动（例如避免驶近的汽车）。然而，由于实验室设置的复杂性，动态声音定位，即我们确定声音在空间中移动时的位置的能力，在很大程度上尚未得到充分研究。该项目的长期目标是了解听觉运动的感知和认知基础，试图协调当前的静态和动态声音定位理论。 我们最近的工作证明了听觉运动在一系列速度范围内的上限，这是以前从未探索过的。基于这项工作，我们假设听觉运动基于连续时间点的静态定位线索的比较，并受到双耳系统的时间分辨率（模糊快照模型）的约束。 但到目前为止，我们的工作重点是使用在水平面上以固定距离旋转的声音进行方位定位。为了检验我们的假设和不同定位线索的相对贡献，我们将把我们的研究扩展到导致强度、直接混响比和多普勒频移变化的轨迹。为此，我们首先需要根据空间音频渲染技术在听众耳朵中保留定位线索的能力来描述其特征。然后我们将系统地研究单耳和双耳定位线索对运动感知的影响。在接下来的几年中，我们将研究空间特征对具有多个同时轨迹的复杂听觉场景中动态声源分组过程的影响。 与此同时，我们将根据人类听众的实验结果来实现声音定位模型。我们将进行逐步复杂化，从固定距离的声音方位角定位的简单模型开始，然后添加运动引起的模糊，然后对距离和速度估计进行建模，最后考虑我们同时跟踪多个声源的能力。在第 5 年，我们将在贝叶斯观察者模型中集成不同的线索以实现最佳预测，类似于用于视觉运动感知的线索。这些预测将与实证结果进行比较，以测试声音定位的替代理论。 在理论基础上，该研究计划将为声音定位的统一理论提供基础。该程序对于空间声音再现（虚拟现实、娱乐、视频会议）、改善助听器的空间功能以及目标声音的声学监测具有实际意义。未来的方向包括通过研究视觉和听觉系统如何提供有关物体运动的补充信息来实现运动感知中的多感官整合。