Analysis of Typefaces Designed for Readers with Developmental Dyslexia - Insights from Neural Networks
Analysis of Typefaces Designed for Readers with Developmental Dyslexia - Insights from Neural Networks
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DOI：
10.1007/978-3-030-57058-3_37
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发表时间：
2020-07
期刊：
影响因子：
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通讯作者：
Xinru Zhu;K. Kageura;S. Satoh
中科院分区：
文献类型：
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作者：
Xinru Zhu;K. Kageura;S. Satoh
发展性阅读障碍是一种特殊的学习障碍，其特点是学习阅读有严重的困难。在各种辅助技术中，有专门为有阅读障碍的读者设计的字体。尽管最近的研究显示了这些字体的有效性，但这些字体的视觉特征对有阅读障碍的读者来说是有益的，这一点还有待揭示。本研究旨在探索使用神经网络来澄清拉丁阅读障碍字体的视觉特征的可能性，并将其应用于其他语言的字体，本研究的对象是日语。作为第一步，我们进行了简单的分类任务，看看CNN是否能识别拉丁阅读障碍字体和标准字体之间的细微差异，以及它是否可以应用于日语字符的分类。结果表明，cnn能够学习拉丁阅读障碍字体的视觉特征，并根据这些特征对日语字体进行分类。这表明了进一步利用神经网络研究跨语言阅读障碍读者字体的可能性。
Developmental dyslexia is a specific learning disability that is characterized by severe difficulties in learning to read. Amongst various supporting technologies, there are typefaces specially designed for readers with dyslexia. Although recent research shows the effectiveness of these typefaces, the visual characteristics of these typefaces that are good for readers with dyslexia are yet to be revealed.This research aims to explore the possibilities of using neural networks to clarify the visual characteristics of Latin dyslexia typefaces and apply those to typefaces in other languages, in this case, Japanese.As a first step, we conducted simple classification tasks to see whether a CNN identifies subtle differences between Latin dyslexia typefaces and standard typefaces, and whether it can be applied to classify Japanese characters.The results show that CNNs are able to learn visual characteristics of Latin dyslexia typefaces and classify Japanese typefaces with those features. This indicates the possibility of further utilizing neural networks for research regarding typefaces for readers with dyslexia across languages.