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: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=757234
• 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.

听觉系统的主要挑战之一是跟踪声音来源，以预测其未来的道路和指导行动（例如，避免使用接近的汽车）。然而，由于实验室设置的并发症，动态的声音定位是我们确定声音在太空中移动时的位置的能力。该计划的长期目标是了解听觉运动的感知和认知基础，以调和静态和动态声音本地化的当前理论。 我们最近的工作表明，在以前从未探索过的一系列速度中，听觉运动的上限存在。基于这项工作，我们假设听觉运动是基于连续时间点的静态定位线索的比较，受双耳系统的时间分辨率（模糊快照模型）的约束。但是，到目前为止，我们的工作集中于方位角定位，使用在水平面上的固定距离旋转的声音。为了检验我们的假设和不同定位线索的相对贡献，我们将扩展到调查到导致强度变化，直接与回响比和多普勒变化的轨迹。为此，我们首先需要根据它们在听众耳朵上保留本地化提示的能力来表征空间音频渲染技术。然后，我们将系统地研究对运动感知的单方和双耳定位线索的影响。在后来的几年中，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的分组过程的影响。 同时，我们将通过与人类听众的实验结果实现声音本地化模型。我们将从进行渐进的络合率开始，从一个简单的固定距离的方位角定位模型开始，然后添加运动引起的模糊，然后进行建模距离和速度估计，最后考虑了我们同时跟踪多种声音源的能力。在第5年，我们将在贝叶斯观察者模型中集成不同的提示，以进行最佳预测，类似于视觉运动感知的预测。预测将与经验发现进行比较，以检验声音定位的替代理论。 从理论上讲，该研究计划将为统一的声音本地化理论提供理由。该程序对空间声音复制（在虚拟现实，娱乐，视频会议中）具有实际影响，用于改善助听器中的空间功能以及对目标声音的声学监视。未来的方向包括通过调查视觉和听觉系统如何提供有关对象运动的互补信息，包括在运动感知中进行多感觉集成。