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Human–computer interaction based visual feedback system for augmentative and alternative communication

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Abstract

The knowledgeable, human–machine interaction sight system has the benefits of low interference, lower permeability, and no interface attachment. The smart vision system has been critical in human–computer interaction to grow and advance technologies and research. The Human–Computer Interaction based Visual Feedback System (HCIVFS) is very quickly relative to the conventional collaborative mode. Such challenges may also affect the smart machine's view and the general use of sensation communication. The fundamental premise of the computer's sight communication architecture requires practical stability. This article explores the quality of the intellectual computer's enabling communication. The Rule of Fitts has also been included in this paper for three points-to-clicks applications. The proposed algorithm's reliability is analyzed in operations, visualization, and computer vision algorithms. There is a fair recommendation for an immersive configuration of the input method for intellectual sight by computer.

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Acknowledgements

This work was sponsored in part by the Research and Practice Project of Higher Education Teaching Reform in Hebei Province in 2017-2018 (2017GJJG295); Scientific research and technological guidance project of colleges and universities in Hebei Province in 2020 (Z2020232); General project supported by the team of Tangshan Normal University in 2020 (2020c13).

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Authors and Affiliations

  1. Department of Computer Science, Tangshan Normal University, Tangshan, 063000, China

    Yubin Liu

  2. Department of Computer Science and Engineering, Adhiyamaan College of Engineering, Hosur, India

    C. B. Sivaparthipan

  3. Amity University, Noida, Uttar Pradesh, India

    Achyut Shankar

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  1. Yubin Liu
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  2. C. B. Sivaparthipan
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  3. Achyut Shankar
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Correspondence to Yubin Liu.

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Yubin Liu, Sivaparthipan, C.B. & Shankar, A. Human–computer interaction based visual feedback system for augmentative and alternative communication. Int J Speech Technol 25, 305–314 (2022). https://doi.org/10.1007/s10772-021-09901-4

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  • DOI: https://doi.org/10.1007/s10772-021-09901-4

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