Assessing penmanship of Chinese handwriting: a deep learning-based approach

IF 2 2区 教育学 Q2 EDUCATION & EDUCATIONAL RESEARCH
Zebo Xu, Prerit S. Mittal, Mohd. Mohsin Ahmed, Chandranath Adak, Zhenguang G. Cai
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Abstract

The rise of the digital era has led to a decline in handwriting as the primary mode of communication, resulting in negative effects on handwriting literacy, particularly in complex writing systems such as Chinese. The marginalization of handwriting has contributed to the deterioration of penmanship, defined as the ability to write aesthetically and legibly. Despite penmanship being widely acknowledged as a crucial factor in predicting language literacy, research on its evaluation remains limited, with existing assessments primarily dependent on expert subjective ratings. Recent initiatives have started to explore the application of convolutional neural networks (CNN) for automated penmanship assessment. In this study, we adopted a similar approach, developing a CNN-based automatic assessment system for penmanship in traditional Chinese handwriting. Utilizing an existing database of 39,207 accurately handwritten characters (penscripts) from 40 handwriters, we had three human raters evaluate each penscript’s penmanship on a 10-point scale and calculated an average penmanship score. We trained a CNN on 90% of the penscripts and their corresponding penmanship scores. Upon testing the CNN model on the remaining 10% of penscripts, it achieved a remarkable performance (overall 9.82% normalized Mean Absolute Percentage Error) in predicting human penmanship scores, illustrating its potential for assessing handwriters’ penmanship. To enhance accessibility, we developed a mobile application based on the CNN model, allowing users to conveniently evaluate their penmanship.

Abstract Image

中文笔迹的笔法评估:基于深度学习的方法
数字时代的兴起导致手写作为主要交流方式的地位下降,从而对手写读写能力产生了负面影响,尤其是在中文等复杂的书写系统中。手写的边缘化导致了书写能力的退化,书写能力是指书写美观、清晰的能力。尽管人们普遍认为书写能力是预测语言素养的关键因素,但对其评估的研究仍然有限,现有的评估主要依赖于专家的主观评价。最近,人们开始探索将卷积神经网络(CNN)应用于自动笔法评估。在本研究中,我们采用了类似的方法,开发了基于卷积神经网络的繁体汉字书写能力自动评估系统。我们利用现有数据库中来自 40 位书写者的 39,207 个准确手写体(笔迹),让三位人类评分员以 10 分制对每个笔迹的笔法进行评估,并计算出平均笔法分数。我们对 90% 的笔迹及其相应的书写评分进行了 CNN 训练。在对剩余 10% 的笔迹进行测试后,CNN 模型在预测人类笔迹评分方面取得了不俗的成绩(总体平均绝对百分比误差为 9.82%),这说明了 CNN 在评估书写者笔迹方面的潜力。为了提高可访问性,我们开发了基于 CNN 模型的移动应用程序,使用户可以方便地评估自己的书写水平。
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来源期刊
CiteScore
5.20
自引率
16.00%
发文量
0
期刊介绍: Reading and writing skills are fundamental to literacy. Consequently, the processes involved in reading and writing and the failure to acquire these skills, as well as the loss of once well-developed reading and writing abilities have been the targets of intense research activity involving professionals from a variety of disciplines, such as neuropsychology, cognitive psychology, psycholinguistics and education. The findings that have emanated from this research are most often written up in a lingua that is specific to the particular discipline involved, and are published in specialized journals. This generally leaves the expert in one area almost totally unaware of what may be taking place in any area other than their own. Reading and Writing cuts through this fog of jargon, breaking down the artificial boundaries between disciplines. The journal focuses on the interaction among various fields, such as linguistics, information processing, neuropsychology, cognitive psychology, speech and hearing science and education. Reading and Writing publishes high-quality, scientific articles pertaining to the processes, acquisition, and loss of reading and writing skills. The journal fully represents the necessarily interdisciplinary nature of research in the field, focusing on the interaction among various disciplines, such as linguistics, information processing, neuropsychology, cognitive psychology, speech and hearing science and education. Coverage in Reading and Writing includes models of reading, writing and spelling at all age levels; orthography and its relation to reading and writing; computer literacy; cross-cultural studies; and developmental and acquired disorders of reading and writing. It publishes research articles, critical reviews, theoretical papers, and case studies. Reading and Writing is one of the most highly cited journals in Education, Educational Research, and Educational Psychology.
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