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Assessment of Reading Material with Flow of Eyegaze Using Low-Cost Eye Tracker

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Computational Intelligence in Pattern Recognition

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 999))

Abstract

Reading text is a complex process involving visual, language, and motor functions. The movement characteristics of eye depend on the understanding of a content. In this paper, we present the methodology of quantifying the difficulty level of a textual content for a silent reading scenario using the eyegaze data captured from low-cost eye-tracking device, EyeTribe. Broadly, two types of contents are chosen such that one is easy to understand and the other is difficult. Standard readability indices are used to benchmark the easiness level of the contents. Experiment is performed with 15 individuals, and eyegaze data is used to quantify the smoothness in the flow of the reading. Statistical features are derived from the adjacency matrix obtained from the successive fixations within and adjacent lines. Results demonstrate statistically significant difference between two types of texts, enabling a set of materials to be relatively graded. A scoring metric based on a mixture of partial sigmoid functions is proposed to quantify the easiness of the text experienced by an individual. The scores reflect that even within the broad category of easy and difficult content, the level of easiness varies between individuals.

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Notes

  1. 1.

    http://www.preservearticles.com/2011080510137/12-short-paragraphs-in-english-language-for-school-kids-free-to-read.html.

  2. 2.

    https://www.enotes.com/topics/great-expectations.

  3. 3.

    https://www.quora.com/Why-is-there-so-much-criticism-for-demonetization-in-India-when-it-is-undoubtedly-a-correct-step.

  4. 4.

    https://www.helsinki.fi/en/research/research-environment/research-ethics.

  5. 5.

    https://www.helsinki.fi/en/research/research-environment/research-ethics.

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Acknowledgements

The clearance on ethical issues for handling and analysis of the data collected has been acquired on October 24, 2017 from Institutional Review Board (IRB) of Tata Consultancy services Ltd. Authors are thankful to the IRB members for conducting the review, monitoring, and approval for the eyegaze-related study. We have followed the Helsinki Human Research guidelines for the data collection.

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Authors and Affiliations

  1. TCS Research and Innovation, Tata Consultancy Services, Ecospace 1B, Kolkata, 700156, India

    Aniruddha Sinha

  2. Computer Science and Engineering, Jadavpur University, Kolkata, 700032, India

    Sanjoy Kumar Saha

  3. Computer Science and Engineering, Indian Institute of Technology, Kharagpur, 721302, India

    Anupam Basu

Authors
  1. Aniruddha Sinha
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  2. Sanjoy Kumar Saha
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  3. Anupam Basu
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Corresponding author

Correspondence to Aniruddha Sinha .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Technology, Indian Institute of Engineering Science and Technology, Howrah, West Bengal, India

    Asit Kumar Das

  2. Department of Computer Science and Engineering, Sri Sivani College of Engineering, Srikakulam, Andhra Pradesh, India

    Janmenjoy Nayak

  3. Department of Computer Application, Veer Surendra Sai University of Technology, Burla, Sambalpur, Odisha, India

    Bighnaraj Naik

  4. Department of Bioinformatics, Maulana Abul Kalam Azad University of Technology, Kolkata, West Bengal, India

    Soumen Kumar Pati

  5. Faculty of Communication Sciences, University of Teramo, Teramo, Italy

    Danilo Pelusi

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Sinha, A., Kumar Saha, S., Basu, A. (2020). Assessment of Reading Material with Flow of Eyegaze Using Low-Cost Eye Tracker. In: Das, A., Nayak, J., Naik, B., Pati, S., Pelusi, D. (eds) Computational Intelligence in Pattern Recognition. Advances in Intelligent Systems and Computing, vol 999. Springer, Singapore. https://doi.org/10.1007/978-981-13-9042-5_42

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