Document Type : Original Research Paper

Authors

Faculty of Electrical and Computer Engineering, Qom University of Technology, Qom, Iran

Abstract

Background and Objective:The mainstream of society has isolated deaf people due to their inability to communicate with the deaf community. Currently, 1,400 deaf people are born in the country every year, most of whom have a hearing family. For this reason, parents in the early years of a child's life, due to unfamiliarity with sign language, cannot teach them a complete model of sign language. As the name implies, sign language uses gestures, or more precisely hand, eye, and standing postures to convey meaning. If, for example, the movement of the mouth or the general state of the face changes, the meaning of the word produced can also change, or in other words, another word is produced. The same principle applies to the movements of the fingers and hands. The most important factor through which human beings can form their relationships and connections is using different methods such as speaking, writing and sign language. The point that deaf or semi-deaf people are ignored in communities is because of their disability in forming intimate relationships, and also the lack of common training according to what is needed in the society. The text to sign language translation systems have been created to resolve communication problems among hearing and deaf persons. Due to unstructured Persian language as well as the problems of Persian sign language, using translators’ systems of other countries is not practicable. The present study seeks to design a system that receives Persian text as an input and changes it to Persian sign language after all the necessary natural language processing is done.
Methods:In doing this matter, several challenges are seen on our way:  a) The number of Persian sign language words which are few compared to the words in Persian language and b) The ambiguity and pun normally used in Persian language. So, similar systems’ architecture could not be applied. Therefore, a new architecture is proposed that uses the relation between the removal pun modules and input text invert module to the deaf world by using designed ontology.
Findings: Using this architecture, the efficiency of the Persian text to Persian sign language translator system has improved to 95% and increased the accuracy of the translator system by tripling.
Conclusion: Sign language interpreter system is designed to connect deaf people with other people in the community. In addition, the sign language translator system can be used to teach sign language. Implementing the Persian sign language translator system has challenges due to its unstructured as well as the problem of ambiguity of some words in Persian, as well as the problems in Persian sign language and the limitations in the number of known movements of this language. The paper addressed the challenges to an acceptable degree by presenting a new architecture. In the new architecture, two modules for recognizing and correcting puns and converting sentences into the world of the deaf have been used. Both modules use their own designed ontology.
 

Keywords

Main Subjects

COPYRIGHTS 
©2019 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers. 

[2] Siavashi S. Persian language and necessity of revision in education and assessment of Iranian deaf. Paper presented in the 1st Conference of Iranian Linguistics Society. Tehran; 2005. Persian.
[3] Shamsfard M. Challenges and Open Problems in Persian Text Processing; 2005. Persian.
[4] Aleahmad. An introduction to semantic web. Tehran: University of Tehran Press; 2007. Persian.
[6] Amiri d Abdoli. Design and implementation of course arak university. Arak: Faculty of Engineering; 2009. Persian.
[14] Dasgupta T, Anupam Basu SD. Prototype machine translation system from text-to-Indian sign. Asian Federation of Natural Language Processing; 2010.
[15] Ombardo V, Battaglino C, Damiano R. An avatar–based interface for the italian sign language. IEEE, Seoul, South Korea; 2011.
[16] Daud A, Khan W, Che D. Urdu language processing: a survey. Department of Computer Science and Software Engineering, Islamabad Pakistan; 2016.
[17]San-segundo R, Montero JM, Co´rdoba R, Sama V, Ferna´ndez F, D’haro LF, Lo´pez-luden˜a V, Sa´nchez D, Carcı´a A. Design, development and field evaluation of a Spanish into sign language translation system. Departamento de Ingeniería Electrónica, Etsi Telecomunicación Universidad Politécnica de Madrid Spain; 2012.
[18] Maritan Ugulino de Araújo T, Lacet Silva Ferreira F, Assis Nobre Dos Santos Silva D, Hermínio Lemos F, Pessoa Neto G. Automatic generation of Brazilian sign language windows for digital TV systems. Digital Video Applications Lab (LAVID), Federal University of Paraiba Brazil; 2013.
[22] Khaleghi G Deaf and sign language, limitations and features; 2010. Persian.
[23] Sstiri A. Natural language processing tools, the fourth annual workshop of web technology Lab, Ferdowsi University of Mashhad; 2012. Persian.
[24] Siavashi S. Deaf education, defending the reference language in education and eliminating discrimination. Journal of Information and Study of Disabilities and Disabilities. 2006; 1: 35-37. Persian.
[25] Bazrafkan M. A review of Persian language processing problems using computer systems. Paper presented in the National Conference on Computer Engineering and Information Technology Management; 2014. Persian.
[26] System analysis automatic find keywords Farsi. Tehrna: IUST Press; 2009. Persian.
[27] Shamsfard M. (2006). Persian text processing: Past achievements, challenges ahead. The second workshop on Farsi and computer; 2006. Persian.
[28] Dokhani. A review of protégé Software. Iranian Electronic Science and Technology Magazine. 2014; 1(7). Persian.
[29] Akramifard A. (2012) Ontology representation. Mashhad: International University of Ferdowsi Press. Persian.
CAPTCHA Image