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Towards a numerically tractable model for the auditory substitution of tactile percepts

机译:建立触觉知觉的听觉替代的数值可控模型

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We refer to channels of communication that link the user to information systems as cognitive communication channels. One especially interesting research topic related to cognitive communication channels deals with a special application called sensory substitution, when information is conveyed through a channel other than the one that is normally used for the given application. Our goal is to develop engineering systems for the remote teleoperation of robots using sensory substitution to convey feedback information in meaningful ways. Such applications could help reduce the cognitive load for the user on the one hand, and help alleviate the effect of control instabilities and hidden parameters on the other. A large part of our research deals with how to provide information on tactile percepts — otherwise inaccessible to the remote user — through sound. In this paper, we present one possible mapping between tactile percepts and auditory parameters. Through a set of controlled experiments, we show that the parameters used are meaningful and the sounds can at some level be learned by users as a substitute for tactile perception. Analyzing the error statistics of the experiments, we argue that it would be worthwhile to create a system in which the sound parameters could be locally tuned to enhance performance on a user-per-user basis. To this end, we convert the analytical descriptions of our sounds into an higher-order singular value decomposition (HOSVD) based tensor product model form. In order to be able to apply a wide range of mathematical analysis tools — such as principal component analysis and user performance-oriented adaptivity — we demonstrate that it is possible to convert our models into such canonical forms.
机译:我们将将用户链接到信息系统的沟通渠道称为认知沟通渠道。当信息通过通常用于给定应用程序的通道之外的其他通道传递信息时,与认知交流通道有关的一个特别有趣的研究主题涉及一种称为感觉替代的特殊应用程序。我们的目标是开发使用感官替代以有意义的方式传达反馈信息的机器人远程遥控操作的工程系统。这种应用一方面可以帮助减轻用户的认知负担,另一方面可以减轻控制不稳定性和隐藏参数的影响。我们的研究很大一部分涉及如何通过声音提供有关触觉感知的信息(否则远程用户无法访问)。在本文中,我们提出了一种可能的触觉知觉和听觉参数之间的映射。通过一组受控实验,我们表明所使用的参数是有意义的,并且用户可以在某种程度上学习声音,以代替触觉感知。通过分析实验的错误统计信息,我们认为创建一个可以对声音参数进行本地调整以提高每个用户的性能的系统是值得的。为此,我们将声音的解析描述转换为基于高阶奇异值分解(HOSVD)的张量积模型形式。为了能够应用广泛的数学分析工具(例如主成分分析和面向用户性能的适应性),我们证明了有可能将我们的模型转换为此类规范形式。

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