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首页> 外文会议>International conference on human-computer interaction;International conference on universal access in human-computer interaction >An Augmented Reality-Based Word-Learning Mobile Application for Children with Autism to Support Learning Anywhere and Anytime: Object Recognition Based on Deep Learning
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An Augmented Reality-Based Word-Learning Mobile Application for Children with Autism to Support Learning Anywhere and Anytime: Object Recognition Based on Deep Learning

机译：自闭症儿童基于增强现实的单词学习移动应用程序，可随时随地支持学习：基于深度学习的对象识别

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摘要

An abundant earlier controlled studies have underscored the importance of early diagnosis and intervention in autism. Over the past several years, thanks to technological advances, we have witnessed a large number of technology-based teaching and learning applications for children with autism. Among them, augmented reality-based ones have gained much attention recently due to its unique benefits of providing multiple learning stimulus for these children via accessing a kinesthetic moving simply using a mobile device. Despite it, few have been developed for these young children in China, which motivates our study. In particular, in this paper, we present a mobile vocabulary-learning application for Chinese autistic children especially for outdoor and home use. The core object recognition module is implemented within the deep learning platform, TensorFlow; unlike other sophisticated systems, the algorithm has to run in an offline fashion. We conducted two small-scale pilot studies to assess the system's feasibility and usability with typically developing children, children with autism, their parents and special education teachers with very promising and satisfying results. Our studies did suggest that the downside of the application is the performance of the object-recognition module. Therefore, before we further examine the benefits of such AR-based learning tools in clinical settings, it is crucial to fine-tune the algorithm in order to improve its accuracy. Despite it, since the current literature of AR-technology on Chinese word-learning for children with special needs is still in its infancy, our studies offers early glimpse into the usefulness, usability and applicability of such AR-based mobile learning application, particularly to facilitate learning at anytime and anywhere.
机译：早期的受控研究强调了早期诊断和干预在自闭症中的重要性。过去几年，由于技术进步，我们目睹了自闭症儿童的大量基于技术的教学和学习应用。其中，由于其通过访问简单地使用移动设备的通知移动，增加了基于现实的基于现实的基于现实的基于现实的基于现实的效果。尽管如此，很少有人为中国的这些幼儿开发，这激励了我们的研究。特别是，在本文中，我们为中国自闭症儿童提供了一个移动词汇学习申请，特别是室外和家庭使用。核心对象识别模块在深度学习平台上实现，TensorFlow;与其他复杂系统不同，该算法必须以离线方式运行。我们进行了两项小型飞行员研究，以评估系统的可行性和可用性，通常发展儿童，自闭症的儿童，父母和特殊教育教师具有非常有前途和令人满意的结果。我们的研究确实表明应用程序的缺点是对象识别模块的性能。因此，在我们进一步检查了临床环境中的基于AR的学习工具的益处之前，这对微调算法至关重要，以提高其准确性。尽管如此，由于AR技术对具有特殊需求的儿童的AR技术的文献仍处于初期的初期，我们的研究提前一睹了基于AR的移动学习申请的有用，可用性和适用性，特别是促进随时随地学习。

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