CFP last date
20 January 2025
Reseach Article

A Cascaded Speech to Arabic Sign Language Machine Translator using Adaptation

by Shereen A. Mohamed, Mohamed A. Abdou, Y. F. Hassan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 133 - Number 5
Year of Publication: 2016
Authors: Shereen A. Mohamed, Mohamed A. Abdou, Y. F. Hassan
10.5120/ijca2016907799

Shereen A. Mohamed, Mohamed A. Abdou, Y. F. Hassan . A Cascaded Speech to Arabic Sign Language Machine Translator using Adaptation. International Journal of Computer Applications. 133, 5 ( January 2016), 5-9. DOI=10.5120/ijca2016907799

@article{ 10.5120/ijca2016907799,
author = { Shereen A. Mohamed, Mohamed A. Abdou, Y. F. Hassan },
title = { A Cascaded Speech to Arabic Sign Language Machine Translator using Adaptation },
journal = { International Journal of Computer Applications },
issue_date = { January 2016 },
volume = { 133 },
number = { 5 },
month = { January },
year = { 2016 },
issn = { 0975-8887 },
pages = { 5-9 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume133/number5/23780-2016907799/ },
doi = { 10.5120/ijca2016907799 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:30:18.392688+05:30
%A Shereen A. Mohamed
%A Mohamed A. Abdou
%A Y. F. Hassan
%T A Cascaded Speech to Arabic Sign Language Machine Translator using Adaptation
%J International Journal of Computer Applications
%@ 0975-8887
%V 133
%N 5
%P 5-9
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cascaded machine translation systems are essential for Deaf people. Speech recognizers and sign language translators when combined together constitute helpful automatic machine translators. This paper introduces an automatic translator from Arabic spoken language into Arabic sign language. This system aims to integrate Deaf students into classrooms of hearing ones. The proposed system consists of three cascaded modules: a modified Arabic speech recognizer that works using adaptation, an Arabic machine translator, and a developed signing avatar animator. The system is evaluated on real case studies and shows good performance.

References
  1. Kennaway, R.,J.Glauert, and I.Zwitserlood(2007). Providing Signed Content on the Internet by Synthesized Animation. In ACM Transactions on Computer-Human Interaction (TOCHI) journal. Volume 14, Issue 3, Article No. 15
  2. Jaballah, K., &Jemni, M. (2013). A Review on 3D Signing Avatars: Benefits, Uses and Challenges. International Journal of Multimedia Data Engineering and Management (IJMDEM), 4(1), 21-45.
  3. Halawani, S. M., Daman, D., Kari, S., & Ahmad, A. R. (2013). An Avatar Based Translation System from Arabic Speech to Arabic Sign Language for Deaf People. International Journal of Computer Science & Network Security,13, 43-52.‏
  4. Almohimeed, A., Wald, M., & Damper, R. I. (2011, July). Arabic text to Arabic sign language translation system for the deaf and hearing-impaired community. In Proceedings of the Second Workshop on Speech and Language Processing for Assistive Technologies (pp. 101-109). Association for Computational Linguistics.‏
  5. Mohandes, M. (2006). Automatic translation of Arabic text to Arabic sign language. AIML Journal, 6(4), 15-19.‏
  6. Caridakis, G., Asteriadis, S., &Karpouzis, K. (2014). Non-manual cues in automatic sign language recognition. Personal and ubiquitous computing, 18(1), 37-46.‏
  7. Dreuw, P., Stein, D., Deselaers, T., Rybach, D., Zahedi, M., Bungeroth, J., & Ney, H. (2008). Spoken language processing techniques for sign language recognition and translation. Technology and Disability, 20(2), 121-133.‏
  8. Stokoe, W. C., Casterline, D. C., &Croneberg, C. G. (1976). A dictionary of American Sign Language on linguistic principles.Linstok Press.‏
  9. Cooper, H. and R. Bowden (2009). Learning Signs from Subtitles: A Weakly Supervised Approach to Sign Language Recognition (2568-2574) Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 22-25 June 2009, Miami, Florida, USA
  10. Efthimiou E, Fotinea SE, Sapountzaki G (2007) Feature-based natural language processing for GSL synthesis. Sign Lang Linguist 10(1):3–23
  11. Kipp, M. Heloir, A. , Nguyen, Q. 2011. Sign Language Avatars: Animation and Comprehensibility.IVA 2011, LNAI 6895, pp. 113-126.
  12. CMUSphinx website: http://cmusphinx.sourceforge.net/. Last access date 20/11/2015
  13. Levenshtein V (1966) Binary codes capable of correcting deletions, insertions, and reversals. Soviet Physics Doklady
  14. Elliott, R., Bueno, J., Kennaway, R., &Glauert, J. (2010, May). Towards the integrationn of synthetic slannimation with avatars into corpus annotation tools. In 4th Workshop on the Representation and Processing of Sign Languages: Corpora and Sign Language Technologies, Valletta, Malta (p. 29).‏
Index Terms

Computer Science
Information Sciences

Keywords

Arabic Sign Language (ArSL) Deaf students Example-based translation system signing avatars