Issue |
E3S Web Conf.
Volume 430, 2023
15th International Conference on Materials Processing and Characterization (ICMPC 2023)
|
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Article Number | 01090 | |
Number of page(s) | 10 | |
DOI | https://doi.org/10.1051/e3sconf/202343001090 | |
Published online | 06 October 2023 |
Sustainable Hand Gesture Recognition for Speech Conversion, Empowering the Speech-Impaired
1 Department of Information technology, GRIET, Bachupally, Hyderabad, JNTUH, Telangana, India, 500090.
2 School of Applied and Life Sciences, Uttaranchal University, Dehradun, 248007, India
* Corresponding author: ledalla.sukanya@gmail.com
A sustainable language disorder affects an individual’s ability to reach out to others through speaking and listening. So utilizing sustainable hand gestures is among the most widespread means of non-verbal and visual communication used by people with speech disabilities worldwide. However, even though sustainable sign language is used everywhere by speech-impaired and hearing-impaired people, most of the populace who don't have any knowledge about sign language face difficulties in sustainably communicating with them. This sustainable problem requires better solutions that can successfully support communication for people with speech disabilities. This sustainable approach will reduce the communication gap for the speech-impaired population. There are many sustainable solutions in the market such as using sensors to make a sustainable device that gives a helpful output. But these sustainable solutions are expensive and not everyone can afford them. We are employing Convolutional Neural Networks to create a sustainable model that is trained on different gestures. This sustainable model enables speech-impaired individuals to convey their information using signs which get converted to human-understandable language, and sustainable voice is given as output. The sustainable hand gestures made are captured as a series of sustainable images which are processed using Python code. This sustainable endeavor introduces a solution that not only automates the identification of sustainable hand gestures but also transforms them into sustainable speech. By interpreting these recognized sustainable gestures, the corresponding recorded audio will be played sustainably. The focus of this sustainable paper is to offer accessibility, convenience, and safety to individuals with speech impairments in a sustainable manner. These sustainable individuals often experience societal discrimination solely due to their disabilities. This sustainable paper is aimed at innovating a sustainable device to help those without the knowledge of sign language sustainably communicate with the people who face difficulty in speech.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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