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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control)
Tazkia Mim Angona
Bangladesh University of Professionals
Computer Science & IT

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Automated Bangla sign language translation system for alphabets by means of MobileNet Tazkia Mim Angona; A. S. M. Siamuzzaman Shaon; Kazi Tahmid Rashad Niloy; Tajbia Karim; Zarin Tasnim; S. M. Salim Reza; Tasmima Noushiba Mahbub
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 3: June 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i3.15311

Abstract

Individuals with hearing and speaking impairment communicate using sign language. The movement of hand, body and expressions of face are the means by which the people, who are unable to hear and speak, can communicate. Bangla sign alphabets are formed with one or two hand movements. There are some features which differentiates the signs. To detect and recognize the signs, analyzing its shape and comparing its features is necessary. This paper aims to propose a model and build a computer systemthat can recognize Bangla Sign Lanugage alphabets and translate them to corresponding Bangla letters by means of deep convolutional neural network (CNN). CNN has been introduced in this model in form of a pre-trained model called “MobileNet” which produced an average accuracy of 95.71% in recognizing 36 Bangla Sign Language alphabets.
Co-Authors A. S. M. Siamuzzaman Shaon Kazi Tahmid Rashad Niloy S. M. Salim Reza Tajbia Karim Tasmima Noushiba Mahbub Zarin Tasnim