PRE2019 3 Group4

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Group 4

Group member Student number Study
Tom Janssen
Ivo Kersten 1233717 Electrical Engineering
Sander van Bommel
Tim Driessen
Rob Vissers 1244863 Electrical Engineering

Problem statement

Objectives

Users

Requirements

Approach

State of the art

[1]

Summary:

[2]

Summary:

[3]

Summary:

[4]

Summary:

[5]

Summary:

[6]

Summary: In general with the production of text entries or smartphones little attention is paid to people with no or impaired vision. Finding the keys for voice control is also an issue for blind people. The newly introduced BrailleEnter will support non-visual interaction with a touchscreen device, since users can tap the screen to raise Braille dots based on Braille coding. When the screen is gently touched, the Braille dots will not rise.

[7]

Summary: From the visually impaired or blind people, being namely 161 million people, only 3% are able to read, write, or count. This is due to the fact that there is lack of Braille reading material in schools. A solution is proposed, where 3D printed visual representations of books are manufactured to improve the learning potential of the target users.

[8]

Summary: Visually impaired individuals are limited in terms of communication, interaction, and personal autonomy due to the lack of Braille literature linked to economic reasons. A portable device is introduced as a reading system for visually impaired individuals, which is based on segmentation, feature extraction, and machine learning for improved accuracy.

[9]

Summary: With the introduction of touchscreens, the accessibility for blind people decreased significantly. Due to the high demands for mobile phones, it is important to also take into account the accessibility for blind people. Research is done to obtain a new way of implementing Braille text in smartphones. From the data of 5 databases, the research is performed.

[10]

Summary: A novel approach to converting Chinese text to Chinese Braille is proposed. A Braille word segmentation model, based on statistical machine leaning, is trained on a Braille corpus, and also on Chinese word segmentation. This will avoid the establishment of syntactic and semantic information rules. Furthermore a statistical model will learn these rules automatically in the background.

Planning

Who is doing what

Week 1

Name Time spent Break-down

References

  1. S. Sultana, A. Rahman, F. H. Chowdhury, and H. U. Zaman, “A novel Braille pad with dual text-to-Braille and Braille-to-text capabilities with an integrated LCD display,” in 2017 International Conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2017, 2018, pp. 195–200, doi: 10.1109/ICICICT1.2017.8342559
  2. V. Argyropoulos, S. Padeliadu, E. Avramidis, T. Tsiakali, and M. Nikolaraizi, “An investigation of preferences and choices of students with vision impairments on literacy medium for studying,” Br. J. Vis. Impair., vol. 37, no. 2, pp. 154–168, May 2019, doi: 10.1177/0264619619838667
  3. M. P. Arakeri, N. S. Keerthana, M. Madhura, A. Sankar, and T. Munnavar, “Assistive Technology for the Visually Impaired Using Computer Vision,” in 2018 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2018, 2018, pp. 1725–1730, doi: 10.1109/ICACCI.2018.8554625
  4. U. Izhar, F. Albermani, D. M. G. Preethichandra, J. Sul, and P. A. J. van Rensburg, “An Electrothermally Actuated MEMS Braille Dot,” in Lecture Notes in Civil Engineering, vol. 37, Springer, 2020, pp. 985–993
  5. S. Hossain et al., “Text to Braille Scanner with Ultra Low Cost Refreshable Braille Display,” in GHTC 2018 - IEEE Global Humanitarian Technology Conference, Proceedings, 2019, doi: 10.1109/GHTC.2018.8601552
  6. M. Alnfiai, S. Sampalli, "BrailleEnter: A Touch Screen Braille Text Entry Method for the Blind," in Procedia Computer Science, vol. 109, 2017, pp. 257-264, doi: 10.1016/j.procs.2017.05.349
  7. L. A. D. Arbes, J. M. J. Baybay, J. E. E. Turingan, and M. J. C. Samonte, "Tagalog text-to-braille translator tactile story board with 3D printing," in IOP Conference Series: Materials Science and Engineering, vol. 482, 2019, doi: 10.1088/1757-899X/482/1/012023
  8. G. B. Holanda et al., "Development of OCR system on android platforms to aid reading with a refreshable braille display in real time," in Measurement: Journal of the International Measurement Confederation, vol. 120, 2018, pp. 150-168, doi: 10.1016/j.measurement.2018.02.021
  9. J. Siqueira et al., "Braille Text Entry on Smartphones: A Systematic Review of the Literature," in Proceeding - International Computer Software and Applications Conference, vol. 2, 2016, pp. 521-526, doi: 10.1109/COMPSAC.2016.74
  10. X. Wang, Y. Yang, J. Zhang, W. Yiang, H. Liu, and Y. Qian, "Chinese to Braille translation based on Braille word segmentation using statistical model," in Journal of Shanghai Jiaotong University (Science), vol. 22, 2017, pp. 82-86, doi: 10.1007/s12204-017-1804-x