Analysis and evaluation of Braille to Text conversion methods

Shokat, Sana and Riaz, Rabia and Rizvi, Sanam Shahla and Khan, Khalil and Riaz, Farina ORCID: and Kwon, Se Jin (2020) Analysis and evaluation of Braille to Text conversion methods. Mobile Information Systems, 2020:3461651. pp. 1-14. ISSN 1574-017X

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Technology is advancing rapidly in present times. To serve as a useful and connected part of the community, everyone is required to learn and update themselves on innovations. Visually impaired people fall behind in this regard because of their inherent limitations. To involve these people as active participants within communities, technology must be modified for their facilitation. This paper provides a comprehensive survey of various user input schemes designed for the visually impaired for Braille to natural language conversion. These techniques are analyzed in detail with a focus on their accessibility and usability. Currently, considerable effort has been made to design a touch-screen input mechanism for visually impaired people, such as Braille Touch, Braille Enter, and Edge Braille. All of these schemes use location-specific input and challenge visually impaired persons to locate specified places on the touch screen. Most of the schemes require special actions to switch between upper and lowercase and between numbers and special characters, which affects system usability. The key features used for accessing the performance of these techniques are efficiency, accuracy, and usability issues found in the applications. In the end, a comparison of all these techniques is performed. Outcomes of this analysis show that there is a strong need for application that put the least burden on the visually impaired users. Based on this survey, a guideline has been designed for future research in this area.

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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Copyright © 2020 Sana Shokat et al. ,is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sep 2019 - 31 Dec 2021)
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sep 2019 - 31 Dec 2021)
Date Deposited: 29 Oct 2021 05:01
Last Modified: 03 Nov 2021 06:28
Fields of Research (2008): 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080107 Natural Language Processing
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4608 Human-centred computing > 460806 Human-computer interaction
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