Dataset of Pakistan Sign Language and Automatic Recognition of Hand Configuration of Urdu Alphabet through Machine Learning.

Autor:	Imran A; Department of Computer Science, Pakistan., Razzaq A; Department of Computer Science, Pakistan., Baig IA; Department of Agribusiness and Applied Economics, Muhammad Nawaz Sharif University of Agriculture, Multan, Pakistan., Hussain A; Department of Computer Science, Pakistan., Shahid S; Department of Computer Science, Pakistan., Rehman TU; Department of Computer Science, Pakistan.
Jazyk:	angličtina
Zdroj:	Data in brief [Data Brief] 2021 Apr 02; Vol. 36, pp. 107021. Date of Electronic Publication: 2021 Apr 02 (Print Publication: 2021).
DOI:	10.1016/j.dib.2021.107021
Abstrakt:	Social correspondence is one of the most significant columns that the public dependent on. Notably, language is the best way to communicate and associate with one another both verbally and nonverbally. There is a persistent communication gap among deaf and non-deaf communities because non-deaf people have less understanding of sign languages. Every region/country has its sign language. In Pakistan, the sign language of Urdu is a visual gesture language that is being used for communication among deaf peoples. However, the dataset of Pakistan Sign Language (PSL) is not available publicly. The dataset of PSL has been generated by acquiring images of different hand configurations through a webcam. In this work, 40 images of each hand configuration with multiple orientations have been captured. In addition, we developed, an interactive android mobile application based on machine learning that minimized the communication barrier between the deaf and non-deaf communities by using the PSL dataset. The android application recognizes the Urdu alphabet from input hand configuration. Competing Interests: The authors have no conflicts of interest to declare (© 2021 The Author(s). Published by Elsevier Inc.)
Databáze:	MEDLINE
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