International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Conversion of Sign Language into Text |
|---|---|
| ABSTRACT | Communication between hearing impaired individuals and normal people is often limited due to the lack of understanding of sign language. This paper presents a real time vision based system for the conversion of sign language into text and voice using computer vision techniques. The proposed system uses a webcam to capture hand gestures, MediaPipe for accurate hand landmark detection, OpenCV for real time image processing, and pyttsx3 for offline text to speech conversion. A predefined set of commonly used hand gestures is recognized based on finger position analysis and mapped to corresponding textual output, which is further converted into audible speech. The system works in real time, does not require any wearable devices, and provides an affordable and user friendly communication aid for hearing and speech impaired individuals. |
| AUTHOR | TRISHA PRASHANT GOSKE, SHRAWANI VITTHAL KUDALE, PIYUSHA DIGAMBAR JADHAV Department of Artificial Intelligence and Machine Learning (TYAN), AISSMS Polytechnic, Pune, Maharashtra, India |
| VOLUME | 181 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1402013 |
| pdf/13_Conversion of Sign Language into Text (3).pdf | |
| KEYWORDS | |
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