SignLingo: Unlock the world of language
Karishma Shravan Rathod
, Bhavik Amit Mehta , Nivedita Rajendra Palan , Manasi Mahadev Sawant , Amit Tiwari
Sign language recognition, Deep learning, Gesture detection, Sign language learning, Mobile application, Indian Sign Language (ISL), American Sign Language (ASL), Image processing.
Sign language is an essential mode of communication for individuals with hearing and speech impairments; however, the lack of accessible learning and recognition tools often creates barriers to broader interaction. This project introduces Sign-Lingo, a mobile application that combines sign language learning, gesture detection, and recognition within a single, user-friendly platform. Utilizing computer vision and deep learning techniques, the app captures hand gestures through the device camera, processes them, and translates them into meaningful words. It offers structured educational content for both American Sign Language (ASL) and Indian Sign Language (ISL), promoting inclusivity and accessibility. By integrating learning and recognition features into one system, Sign-Lingo provides an effective solution for enhancing communication and supporting sign language education across diverse communities.
Volume 12
Issue 4,
April-2025
Pages : b87-b94
Paper Reg. ID: TIJER_157676
Published Paper Id: TIJER2504152
Downloads: 000274
Research Area: Science and Technology
Country: Mumbai, Maharashtra, India
ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: TIJER (IJ Publication) Janvi Wave
