Document recognition and vocalization technology for facilitation of learning process of people with vision impairments

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Abstract

Access to documented information is one of the biggest challenges for adaptation of people with vision impairments in the current computerized society. The main source of awareness in this so-called information space is just text matter. Despite of a big deal of e-sources, it is still widespread situation that texts are available in printed version only. One can by no means always obtain required information from books in Braille writing. Besides, usual printed texts and a part of browseable ones are unavailable for people with vision impairments, though those texts provide access to the vast majority of text data. Therefore, design of soft and hardware enabling blind people to get access to those sources is highly topical nowadays. The given piece of work presents cutting-edge technology of text proceeding for people with vision impairment, which integrates scanning, recognition and vocalization tools.

General Information

Keywords: image recognition, neural networks, wavelet-conversion, Hamming networks, image recovery

Journal rubric: Clinical and Special Psychology

For citation: Kuravsky L.S., Yuryev G.A. Document recognition and vocalization technology for facilitation of learning process of people with vision impairments. Psikhologicheskaya nauka i obrazovanie = Psychological Science and Education, 2009. Vol. 14, no. 5, pp. 73–80. (In Russ., аbstr. in Engl.)

References

  1. Bogomolov A. M. Lichnostnyj adaptacionnyj potencial v kontekste sistemnogo analiza // Psihologicheskaja nauka i obrazovanie. 2008. № 1.
  2. Kuravsky L. S., Baranov S. N., Bulanova O. E., Kravchuk T. E. Nejrosetevaja tehnologija diagnostiki patologicheskih sostojanij po anomalijam
    jelektrojencefalogramm // Nejrokomp’jutery: razrabotka i primenenie. 2007. № 4.
  3. Kuravsky L. S. , Baranov S. N. Wavelet transforms and relaxation neural networks as promising technology components of technical and medical diagnostics and monitoring. In: Proc. 2-nd World Congress on Engineering Asset Management and 4th International Conference on Condition Monitoring. Harrogate. United Kingdom. June 2007.
  4. Kuravsky L. S. , Baranov S. N. Technical diagnostics and monitoring based on capabilities of wavelet transforms and relaxation neural networks // Insight. March 2008. Vol. 50. № 3.

Information About the Authors

Lev S. Kuravsky, Doctor of Engineering, professor, Dean of the Computer Science Faculty, Moscow State University of Psychology and Education, Moscow, Russia, ORCID: https://orcid.org/0000-0002-3375-8446, e-mail: l.s.kuravsky@gmail.com

Grigory A. Yuryev, PhD in Physics and Matematics, Associate Professor, Head of Department of the Computer Science Faculty, Leading Researcher, Youth Laboratory Information Technologies for Psychological Diagnostics, Moscow State University of Psychology and Education, Moscow, Russia, ORCID: https://orcid.org/0000-0002-2960-6562, e-mail: g.a.yuryev@gmail.com

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