Implementation Hand Sign Detection and Recognition with Help of Machine Learning
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Implementation Hand Sign Detection and Recognition with Help of Machine LearningAbstract
Addressing the issues of People with Hearing and Vocal Impairment through a single aiding system is a tough job. A lot of work in modern day research focuses on addressing the issues of one of the above challenges but not all. The work focuses on finding a unique technique based on the machine learning that aids the mute by letting them hear what is represented as text and its sound. The proposed system achieved the technique that takes the sign image through a web camera and applies to the image processing then analysis what exactly want to the mute people at end the text available to voice signals. All these three solutions were modulated to be in a single unique system. All these activities are coordinated using the Ubuntu system using python. The vocally impaired people are helped by the process in which the image to text and text to speech is given using machine learning.
References
- Vigneshwaran S, Shifafathimam, ”Hand Gesture Recognition And Voice Conversion System For Dump People”, IEEE 2019.
- Trung-Hieu Le, Thanh-Hai Tran, Cuong Pham, “The Internet-of-Things based hand gestures using wearable sensors for human machine interaction” IEEE 2019.
- Rajit Nair Dileep Kumar Singh Ashu Shivam Yadav Sourabh Bakshi, “Hand Gesture Recognition system for physically challenged people using IoT” IEEE. 2020.
- Vasileios Sideridis, Andrew Zacharakis, George Tzagkarakis, and Maria Papadopouli, “Gesture Keeper: Gesture Recognition for Controlling Devices in IoT Environments”, IEEE 2019.
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