Skip to main content

Kalema: Digitizing Arabic Content for Accessibility Purposes Using Crowdsourcing

  • Conference paper
Computational Linguistics and Intelligent Text Processing (CICLing 2015)

Abstract

In this paper, we present “Kalema”, a system for digitizing Arabic scanned documents for the visually impaired such that it can be converted to audio format or Braille. This is done through a GWAP which offers a simple, challenging game that helps attract many volunteers for this cause. We show how such a tedious task can be achieved accurately and easily through the use of crowdsourcing.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Library fire in Egypt clashes destroys ’irreplaceable’ 200-year-old documents, http://edition.cnn.com/2011/12/17/world/africa/egypt-unrest

  2. ABBYY. OCR System, http://abbyy.com (2008) (Online; accessed May 19, 2014)

  3. von Ahn, L.: Games with a Purpose. Computer 39(6), 92–94 (2006)

    Article  Google Scholar 

  4. Alkafif, S.: Social initiative to digitize Arabic content (2011), https://www.facebook.com/sadik.alkafif (Online; accessed May 19, 2014)

  5. Bakry, M., Khamis, M., Abdennadher, S.: Arecaptcha: Outsourcing arabic text digitization to native speakers. In: 11th IAPR International Workshop on Document Analysis Systems (DAS), pp. 304–308 (April 2014)

    Google Scholar 

  6. Bazzi, I., Schwartz, R., Makhoul, J.: An omnifont open-vocabulary ocr system for english and arabic. IEEE Transactions on Pattern Analysis and Machine Intelligence 21(6), 495–504 (1999)

    Article  Google Scholar 

  7. Google. Tesseract OCR (2006), http://code.google.com/p/tesseract-ocr/ (Online; accessed May 19, 2014)

  8. Finnish National Library. Digitalkoot (2011), http://www.digitalkoot.fi/ (Online; accessed May 19, 2014)

  9. Märgner, V., El Abed, H.: Guide to OCR for Arabic Scripts. Springer-Verlag, London (2021)

    Google Scholar 

  10. World Health Organization. Visual impairment and blindness (2013), http://www.who.int/mediacentre/factsheets/fs282/en/ (Online; accessed May 19, 2014)

  11. Smith, R.: An overview of the tesseract ocr engine. In: Proceedings of the Ninth International Conference on Document Analysis and Recognition, ICDAR 2007, vol. 02, pp. 629–633. IEEE Computer Society, Washington, DC (2007)

    Google Scholar 

  12. Smith, R., Antonova, D., Lee, D.-S.: Adapting the Tesseract Open Source OCR Engine for Multilingual OCR. In: Proceedings of the International Workshop on Multilingual OCR, MOCR 2009, pp. 1:1–1:8. ACM, New York (2009)

    Google Scholar 

  13. Von Ahn, L.: Human Computation. PhD thesis, Pittsburgh, PA, USA, AAI3205378 (2005)

    Google Scholar 

  14. von Ahn, L., Dabbish, L.: Labeling images with a computer game. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI 2004, pp. 319–326. ACM, New York (2004)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Gasser Akila .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Akila, G., El-Menisy, M., Khaled, O., Sharaf, N., Tarhony, N., Abdennadher, S. (2015). Kalema: Digitizing Arabic Content for Accessibility Purposes Using Crowdsourcing. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2015. Lecture Notes in Computer Science(), vol 9042. Springer, Cham. https://doi.org/10.1007/978-3-319-18117-2_49

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-18117-2_49

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18116-5

  • Online ISBN: 978-3-319-18117-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics