Book ChapterDOI
Effect of Devanagari Font Type in Reading Comprehension: An Eye Tracking Study
Chetan Ralekar,Punyajoy Saha,Tapan K. Gandhi,Santanu Chaudhury,Santanu Chaudhury +4 more
- pp 136-147
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TLDR
There is a scope for improvement in the reading comprehension, by changing the physical properties of the document without changing its content, when the same document is read in different font type.Abstract:
In this world of digitization, screen reading has grown immensely due to the availability of affordable display devices. Most of the people prefer to read on display devices as compared to the print media. To make the reading experience of the reader pleasant and comfortable, the font designers strive hard to choose suitable typographical properties of the text such as font type, font size etc. Some of the researchers suggest that the typography of the text affects the reading performance of the readers to some extent. However, the research focusing on the effect of typography on the reading behavior of the readers is limited and it is hardly touched upon for the Indian scripts. Therefore, the proposed paper aims to find out the effect of Devanagari font type on the reading performance, especially reading comprehension of the readers. In addition to this, a method to reduce the error in the gaze estimation of the eye tracker is also proposed. In order to understand the reading behavior, an eye tracking experiment is performed on 14 participants asking them to read 22 pages, in 3 different font types, presented on the screen of the eye tracker. The performance of the readers is analyzed in terms of total reading time, comprehension score, number of fixations, fixation duration and number of regressions. Our results show that there is a significant difference in the fixation duration, a number of fixations and the comprehension score, when the same document is read in different font type. Thus, there is a scope for improvement in the reading comprehension, by changing the physical properties of the document without changing its content. These findings might be useful to understand the readers’ preference for the font and to design a proper font type for online reading.read more
Citations
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Proceedings ArticleDOI
Intelligent Identification of Ornamental Devanagari Characters Inspired by Visual Fixations
TL;DR: It is found that the convolutional neural network performs better when trained with the assistance of fixation information compared to the network trained without eye fixations.
Journal ArticleDOI
Comparison of the printing areas for commonly used font types: example of green information
TL;DR: The printing area of the 10 commonly used fonts were examined with image processing methods and compared among each other and it was found that Comic Sans MS and Verdana used almost two times the printing area according to the font Courier New.
Proceedings ArticleDOI
Collaborative Human Machine Attention Module for Character Recognition
TL;DR: Wang et al. as mentioned in this paper proposed a collaborative human and machine attention module which considers both visual and network's attention, which can be integrated with any convolutional neural network (CNN) model.
Proceedings ArticleDOI
Human Visual Learning Inspired Effective Training Methods
TL;DR: The results show that the performance of the network improves significantly when trained iteratively with increasing level of blur, and the model trained on gradually decreasing blurriness on Dog vs Cat dataset for classification task.
Posted Content
Understanding Character Recognition using Visual Explanations Derived from the Human Visual System and Deep Networks
TL;DR: In this article, the congruence of information gathering strategies between humans and deep neural networks has been examined in a character recognition task, where the authors use the visual fixation maps obtained from the eye-tracking experiment as a supervisory input to align the model's focus on relevant character regions.
References
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Journal ArticleDOI
Eye movements in reading and information processing: 20 years of research.
TL;DR: The basic theme of the review is that eye movement data reflect moment-to-moment cognitive processes in the various tasks examined.
Proceedings ArticleDOI
Identifying fixations and saccades in eye-tracking protocols
TL;DR: A taxonomy of fixation identification algorithms is proposed that classifies algorithms in terms of how they utilize spatial and temporal information in eye-tracking protocols in order to evaluate and compare these algorithms with respect to a number of qualitative characteristics.
A Comparison of Popular Online Fonts: Which Size and Type is Best?
TL;DR: In this paper, the performance and preference of twelve different fonts at the 12-point size were compared at the 10-, 12-, and 14-point sizes, and the results showed that the larger size of the fonts had a greater effect on reading effectiveness, reading time, perceptions of font legibility, font attractiveness, and general preference.
Journal ArticleDOI
Using Reading Times and Eye-Movements to Measure Cognitive Engagement
TL;DR: The use of eye-movement data is based on a number of assumptions, including the assumption that people look longer at words and images because they are thinking about those objects more as mentioned in this paper.
Journal ArticleDOI
Using Eye Movements to Evaluate the Cognitive Processes Involved in Text Comprehension
TL;DR: The present article describes how to use eye tracking methodologies to study the cognitive processes involved in text comprehension, and much of the information presented can be applied to any study in which participants read verbal stimuli.