Modeling Expertise in Assistive Navigation Interfaces for Blind People

Modeling Expertise in Assistive Navigation Interfaces for Blind People
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盲人辅助导航界面的建模专业知识

DOI:
10.1145/3172944.3173008
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发表时间:
2018
期刊:
International Conference on Intelligent User Interfaces
影响因子:
--
通讯作者:
Asakawa, Chieko
Asakawa, Chieko
中科院分区:
--
文献类型:
--
作者:
Ohn-Bar, Eshed;Guerreiro, João;Ahmetovic, Dragan;Kitani, Kris M.;Asakawa, Chieko

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评估专业知识和路线知识对任务绩效的影响,可以指导智能自适应导航界面的设计。在盲人辅助室内导航界面方面的专业知识相对较少。为了量化用户?S行走模式、路线学习和界面适应之间的复杂关系,我们对8名盲人参与者进行了研究。参与者在使用基于智能手机的逐个转弯导航应用程序时重复了一系列导航任务。结果表明,用户技能和知识在整个路径重复过程中逐渐演化,显著影响任务完成时间。除了探索性分析之外,我们还提出了一种基于个性化递归神经网络的行为模型,用于专家级别的分类,从而朝着根据用户?S的需求定制导航界面迈出了一步。
Evaluating the impact of expertise and route knowledge on task performance can guide the design of intelligent and adaptive navigation interfaces. Expertise has been relatively unexplored in the context of assistive indoor navigation interfaces for blind people. To quantify the complex relationship between the user»s walking patterns, route learning, and adaptation to the interface, we conducted a study with 8 blind participants. The participants repeated a set of navigation tasks while using a smartphone-based turn-by-turn navigation guidance app. The results demonstrate the gradual evolution of user skill and knowledge throughout the route repetitions, significantly impacting the task completion time. In addition to the exploratory analysis, we take a step towards tailoring the navigation interface to the user»s needs by proposing a personalized recurrent neural network-based behavior model for expertise level classification.
DOI: 10.1177/0145482x9709100405
发表时间: 1997
影响因子: 1.1
作者:
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