Recent Advances in Sign Language Detection: A Brief Survey

Download This Paper Open PDF in Browser Add Paper to My Library Share: Permalink Using these links will ensure access to this page indefinitely Copy URL Recent Advances in Sign Language Detection: A Brief Survey 8 Pages Posted: 12 Jul 2022 See all articles by Neha ChallaNeha ChallaSharda University - Department of Computer ScienceKriti BaishyaSharda University - Department of Computer ScienceVinayak RohatgiSharda University - Department of Computer ScienceKeshav GuptaSharda University - Department of Computer ScienceDanish AtherSharda University - Department of Computer ScienceDharm RajSharda University - Department of Computer Science There are 2 versions of this paper Recent Advances in Sign Language Detection: A Brief Survey Number of pages: 8 Posted: 12 Jul 2022 You are currently viewing this paper Downloads 3 Recent Advances in Sign Language Detection: A Brief Survey Number of pages: 8 Posted: 12 Jul 2022 Downloads 3 Date Written: July 14, 2022 Abstract The phenomena related to the domain of detecting an individual's sign gestures and converting it into text in real-time has been an elucidating outlook for the people possessing disabilities. The diversity of researches is in existence for contemplating and actuating the ideation. Varied methodologies have also been induced for amalgamation of sign gesture detection with text-to-speech enabling the possibilities of helping the ones in need. Through this aid, they can convey their message through sign language which can be easily understood by people unfamiliar with it after converting it into text and thus devices that can convert this text to speech may also be developed. In this paper, we've tried to collate various modus operandi's revolving around such approaches and also scrutinized over it for displaying comparative perspective. Keywords: American Sign Language (ASL), Indian Sign Language (ISL), OpenCV. Machine Learning , Deep Learning Suggested Citation: Suggested Citation Challa, Neha and Baishya, Kriti and Rohatgi, Vinayak and Gupta, Keshav and Ather, Danish and Raj, Dharm, Recent Advances in Sign Language Detection: A Brief Survey (July 14, 2022). Available at SSRN: https://ssrn.com/abstract=4157565 Neha Challa (Contact Author) Sharda University - Department of Computer Science ( email ) Gr. Noida, 201306India Kriti Baishya Sharda University - Department of Computer Science ( email ) Gr. Noida, 201306India Vinayak Rohatgi Sharda University - Department of Computer Science ( email ) Gr. Noida, 201306India Keshav Gupta Sharda University - Department of Computer Science ( email ) Gr. Noida, 201306India Danish Ather Sharda University - Department of Computer Science ( email ) Gr. Noida, 201306India Dharm Raj Sharda University - Department of Computer Science ( email ) Gr. Noida, 201306India Download This Paper Open PDF in Browser Do you have a job opening that you would like to promote on SSRN? Place Job Opening Paper statistics Downloads 3 Abstract Views 5 PlumX Metrics Related eJournals Advancement in Electronics & Communication Engineering 2022 (AECE 2022) Follow Advancement in Electronics & Communication Engineering 2022 (AECE 2022) Subscribe to this free journal for more curated articles on this topic FOLLOWERS 3 PAPERS 0 Feedback Feedback to SSRN Feedback (required) Email (required) Submit If you need immediate assistance, call 877-SSRNHelp (877 777 6435) in the United States, or +1 212 448 2500 outside of the United States, 8:30AM to 6:00PM U.S. Eastern, Monday - Friday. Submit a Paper Section 508 Text Only Pages SSRN Quick Links SSRN Solutions Research Paper Series Conference Papers Partners in Publishing Jobs & Announcements Newsletter Sign Up SSRN Rankings Top Papers Top Authors Top Organizations About SSRN SSRN Objectives Network Directors Presidential Letter Announcements Contact us FAQs Copyright Terms and Conditions Privacy Policy We use cookies to help provide and enhance our service and tailor content. To learn more, visit Cookie Settings. This page was processed by aws-apollo5 in 0.252 seconds