A Process to Develop Sign Language Corpus using Crowdsourcing
Uzma Farooq1, Mohd Shafry Mohd Rahim2, Adnan Abid3, Nabeel Sabir Khan4
1Uzma Farooq, Department of Computing, Universiti Teknologi Malaysia, Malaysia.
2Mohd Shafry Bin Mohd Rahim, Department of Computing, Universiti Teknologi Malaysia, Malaysia.
3Adnan Abid*, Department of Computer Science, University of Management and Technology, Pakistan.
4Nabeel Sabir, Department of Computer Science, University of Management and Technology, Pakistan.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 24, 2020. | Manuscript published on March 10, 2020. | PP: 2098-2103 | Volume-9 Issue-5, March 2020. | Retrieval Number: E2975039520/2020©BEIESP | DOI: 10.35940/ijitee.E2975.039520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Humans use language in order to communicate between one another. There exist a number of languages which are either spoken or written. Among these languages, there exists a special type of language called Sign Language (SL). Sign language is a general term which includes any kind of gestural language that makes use of signs and gestures to convey message. Although the deaf community feels comfortable while using Sign Language as their mode of communication, but they face a lot of problems as well. Therefore, in order to help and assist the deaf community a repository of different sign languages are essential for each sign language. This work presents a process to develop a repository by collecting and validating sign language gestures of any language by involving the deaf community and language experts. A small data collection based on a proof-of-concept application has also been presented in this work. Lastly, it highlights the benefits of such corpus by discussing possible applications that can be built to serve the deaf community of the world at large.
Keywords: Crowdsourcing, Sign language, Sign language Corpus, Sign language Standardization.
Scope of the Article: Natural Language Processing