Assessing the Efficiency of Using Augmented Reality for Learning Sign Language

  • Ines KožuhEmail author
  • Simon Hauptman
  • Primož Kosec
  • Matjaž Debevc
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9176)


In this study we examined whether the success rate regarding accuracies of signing particular words differs when the signs for the words are acquired either from (a) a picture symbolizing a sign, (b) an Augmented Reality mobile application, or (c) a physically present sign language interpreter. We analyzed whether any differences would appear between the 25 people included in an experiment. We used three pairs of words and the participants were accordingly classified into three groups. Each group was asked to sign one pair of words based on acquiring signs either from pictures, the Augmented Reality mobile application or a sign language interpreter. When the participants signed single words, their accuracies (=success rates) were evaluated by two sign language interpreters. The results revealed the lowest success rates when watching pictures, while the success rates improved by 35 % when using the Augmented Reality mobile application. When a sign-language interpreter signed words the participants’ success rates in signing increased by an additional 9 %. No differences were found between D/HH signers and hearing non-signers. Generally, participants were the least successful when signing the words “break” and “claw”.


Deaf Hard of hearing Augmented reality Sign language 



We thank D/HH and hearing people for participating in the study, sign-language interpreters and representatives of the Association of the Deaf and Hard of Hearing Podravje, Maribor. Special thanks go to the Slovenian Association of the Deaf and Hard of Hearing for their permission to use the material from the Visual dictionary of Slovenian sign-language during our experiment. The study was supported by the Slovenian Research Agency [no. 1000-11-310140] under The Young Researcher Programme.


  1. 1.
    Carmigniani, J., Furht, B., Anisetti, M., Ceravolo, P., Damiani, E., Ivkovic, M.: Augmented reality technologies, systems and applications. Multimed. Tools Appl. 51, 341–377 (2011)CrossRefGoogle Scholar
  2. 2.
    Fecich, S.: The use of augmented reality-enhanced reading books for vocabulary acquisition with students who are diagnosed with special needs. The Pennsylvania State University (2014)Google Scholar
  3. 3.
    Jones, M., Bench, N., Ferons, S.: Vocabulary acquisition for deaf readers using augmented technology. In: 2nd Workshop on Virtual and Augmented Assistive Technology, 30 March, Minneapolis, Minnesota, USA (2014)Google Scholar
  4. 4.
    Lange, B.S., Requejo, P., Flynn, S.M., Rizzo, A.A., Cuevas, F.J., Baker, L., Winstein, C.: The potential of virtual reality and gaming to assist successful aging with disability. J. Phys. Med. Rehab. Clin. North America 21(2), 339–356 (2010)CrossRefGoogle Scholar
  5. 5.
    Project Das Deaf Magazine (2014).
  6. 6.
    Zainuddin, N.M., Zaman, H.B.: Augmented reality in science education for deaf students: preliminary analysis. In: Regional Conference on Special Needs Education, Faculty of Education, Malaya University (2009)Google Scholar
  7. 7.
    Maxwell-McCaw, D., Zea, M.C.: The deaf acculturation scale (DAS): development and validation of a 58-item measure. J. Deaf Stud. Deaf Educ. 16, 325–342 (2011)CrossRefGoogle Scholar
  8. 8.
    Debevc, M., Kosec, P., Holzinger, A.: Improving multimodal web accessibility for deaf people: sign language interpreter module (SLIM). Multimed. Tools Appl. 45(1), 181–199 (2010)Google Scholar
  9. 9.
    Kožuh, I.: The Deaf and Hard of Hearing on Social Networking Sites: Identities, Community Building and Connections between Communities. [Gluhi in naglušni na spletnih družbenih omrežjih: identiteta, grajenje skupnosti in povezave med skupnostmi.]. Doctoral Dissertation (2015, in press)Google Scholar
  10. 10.
    Lee, S., Henderson, V., Hamilton, H., Starner, T., Brashear, H., Hamilton, S.: A gesture-based American sign language game for deaf children. In: CHI 2005 Extended Abstracts on Human Factors in Computing Systems, pp. 1589–1592 (2005)Google Scholar
  11. 11.
    Tabachnick, G.G., Fidell, L.S.: Experimental Designs Using ANOVA. Duxbury, Belmont (2007)Google Scholar
  12. 12.
    Howell, D.: Statistical Methods for Psychology. Duxbury, Pacific Grove (2002)Google Scholar
  13. 13.
    Kožuh, I., Hintermair, M., Holzinger, A., Volčič, Z., Debevc, M.: Enhancing universal access: deaf and hard of hearing people on social networking sites. Univers. Access Inf. Soc., 1–9 (2014)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Ines Kožuh
    • 1
    Email author
  • Simon Hauptman
    • 1
  • Primož Kosec
    • 2
  • Matjaž Debevc
    • 1
  1. 1.Faculty of Electrical Engineering and Computer ScienceUniversity of MariborMariborSlovenia
  2. 2.NuimoKamnicaSlovenia

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