Current Volume 7
Abstract
A technical device called "Sign Language Detection with Voice" attempts to help people with hearing problems communicate more effectively. This project aims to recognize and translate sign language motions into spoken or written language by applying cutting edge AI and machine learning. This project has the potential to improve inclusivity and accessibility, close the gap between the hearing and deaf communities, and demonstrate the ability of technology to promote harmony and understanding. Through our app, we will be able to gather and analyze patient data to identify prevalent diseases, provide quick and detailed diagnostic reports, and ensure easy and seamless interaction with the app. By concentrating on these results, we may significantly enhance the availability and quality of healthcare in rural areas, hence enhancing the general well-being of the rural populace. This effort is a big step toward making the world more accessible and inclusive for people who have hearing loss. It has the potential to enhance the quality of life for individuals who depend on sign language as their major means of communication by translating and understanding sign language into spoken or written forms. We hope to contribute to a society where communication is unrestricted and where everyone, regardless of hearing ability, can connect and interact with the world more easily by utilizing the most recent developments in AI and voice recognition.
Citations
IRE Journals:
Uday Shekar Biradar , Hemalatha D , Mahesh D M , Tejkumar S
"Enhancing Sign Language Detection for Improved Accessibility" Iconic Research And Engineering Journals Volume 7 Issue 7 2024 Page 396-399
IEEE:
Uday Shekar Biradar , Hemalatha D , Mahesh D M , Tejkumar S
"Enhancing Sign Language Detection for Improved Accessibility" Iconic Research And Engineering Journals, 7(7)
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