一种用于训练回声定位的移动应用程序,该应用程序具有空间渲染回声的新方法

M. Bujacz, Krzysztof Matysik, Grzegorz Górski
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引用次数: 0

摘要

在这篇简短的演示论文中,我们希望展示一个为Android和iOS开发的移动应用程序,目的是训练盲人的回声定位技能和一般听力敏锐度。作为Echovis研究项目的一部分,应用程序中的任务是基于盲人和视力正常的志愿者进行的真实回声定位测试,主要包括猜测距离一到三米的小墙的方向和距离。应用程序中的声音来自双耳录音和使用DearVR和自定义定向回声过滤器的人工渲染。开发的路点声学刺激(WAS)算法允许利用移动处理器的计算能力渲染空间房间回声。WAS算法还用于创建更复杂的训练场景的渲染,例如玩家可以使用回声导航的办公楼。对应用程序的测试表明,尽管在真实场景中的表现略好于使用录音或渲染的测试,但两者之间没有统计学上的显著差异,并且应用程序中的声音足以证明视力和失明测试者的回声定位水平都是非随机的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A mobile application for training echolocation with a novel method for spatially rendered echoes
In this short demo paper we wish to present a mobile application developed for both Android and iOS for the purpose of training echolocation skills and general listening acuity of blind persons. The tasks in the app were based on real echolocation tests performed by blind and sighted volunteers as part of the Echovis research project and primarily consisted of guessing the direction and distance to a small wall at distances from one to three meters. The sounds in the app come from binaural recordings and artificial renders using DearVR and custom directional echo filters. The developed Waypoint Acousitic Stimulation (WAS) algorithm allows to render spatial room echoes with the computational power of a mobile processor. The WAS algorithm was also used to create renders of more complex training scenes, such as an office building through which a player could navigate using echoes. Tests of the app show that although the performance in real scenes is slightly better than tests using recordings or renders, there is no statistically significant difference between them and the sounds in the app are sufficient to demonstrate non-random levels of echolocation in both sighted and blind testers.
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