scholarly journals A Real Time Sign Language Recognition System using Hand Tracking

IJIREEICE ◽  
2021 ◽  
Vol 9 (7) ◽  
Author(s):  
Mrs Smitha P ◽  
Bhuvanashree R ◽  
Jyothi K.N
Keyword(s):  
Real Time ◽  
Sign Language ◽  
Recognition System ◽  
Hand Tracking ◽  
Language Recognition ◽  
Sign Language Recognition

Hear Sign Language: A Real-time End-to-End Sign Language Recognition System

2020 ◽  
pp. 1-1
Author(s):  
Zhibo Wang ◽  
Tengda Zhao ◽  
Jinxin Ma ◽  
Hongkai Chen ◽  
Kaixin Liu ◽  
...  
Keyword(s):  
Real Time ◽  
Sign Language ◽  
Recognition System ◽  
Language Recognition ◽  
Sign Language Recognition ◽  
End To End

scholarly journals Sign Language to Text-Speech Translator Using Machine Learning

2021 ◽  
Vol 9 (7) ◽  
pp. 912-916
Keyword(s):  
American Sign Language ◽  
Sign Language ◽  
New Technologies ◽  
Recognition System ◽  
Hand Tracking ◽  
Language Recognition ◽  
Text To Speech ◽  
Sign Language Recognition ◽  
Cross Platform ◽  
Almost All

Communication with deaf and dumb people is quite difficult task for others. So, through sign language can communicate with deaf and mute persons but it is difficult for normal people to understand the sign language hence it creates a huge gap between them and it's uneasy to exchange their ideas, thoughts with others. This gap has existed for years in order to minimize this, new technologies should be emerged. Therefore, an interpreter is necessary which acts as a bridge between deaf-mute and others. This paper proposed system which is a sign language translator. The system used American Sign Language (ASL) dataset which is pre-processed based on threshold and intensity. This system recognizes sign language alphabet and by joining the letters it creates a sentence then it converts the text to speech. As the system is based on hand, hand gesture is used in sign language recognition system, for that the efficient hand tracking technique which is given by media pipe cross platform is used and it exactly detects the hand after that by using the ANN architecture the model has trained and which classifies the images. The system has achieved 74% accuracy and recognize almost all the letters. The system which also converts sign text to speech so that it will also helpful for blind people.

scholarly journals A Real-Time American Sign Language Recognition System using Convolutional Neural Network for Real Datasets

TEM Journal ◽  
2020 ◽  
pp. 937-943
Author(s):  
Rasha Amer Kadhim ◽  
Muntadher Khamees
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
American Sign Language ◽  
Real Time ◽  
Sign Language ◽  
Recognition System ◽  
High Accuracy ◽  
American Sign ◽  
Language Recognition ◽  
Sign Language Recognition

In this paper, a real-time ASL recognition system was built with a ConvNet algorithm using real colouring images from a PC camera. The model is the first ASL recognition model to categorize a total of 26 letters, including (J & Z), with two new classes for space and delete, which was explored with new datasets. It was built to contain a wide diversity of attributes like different lightings, skin tones, backgrounds, and a wide variety of situations. The experimental results achieved a high accuracy of about 98.53% for the training and 98.84% for the validation. As well, the system displayed a high accuracy for all the datasets when new test data, which had not been used in the training, were introduced.

Based on wearable sensory device in 3D-printed humanoid: A new real-time sign language recognition system

Measurement ◽  
2021 ◽  
Vol 168 ◽  
pp. 108431
Author(s):  
M.A. Ahmed ◽  
B.B. Zaidan ◽  
A.A. Zaidan ◽  
Mahmood M. Salih ◽  
Z.T. Al-qaysi ◽  
...  
Keyword(s):  
Real Time ◽  
Sign Language ◽  
Recognition System ◽  
Language Recognition ◽  
Sign Language Recognition ◽  
3D Printed
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