Sign Language Interpreter

EasyChair Preprint 15930

Abstract

This article unveils an ingenious technology that enables the interpretation of sign lan- guage, which is crucial for communication of the deaf and hard of hearing. This project uses latest technology like computer vision and deep learning to turn hand movements into text in real time. The system consists of a secured database for storing sign language data that improves model accuracy and scal- ability. The introduction of this project was under the chairing of Dr. Pooja Bhatt and the collaboration of Mohammad Awad Baig, Rayapati Bhanu Prakash, Sai Sri Harsha In- jam, and Gunturu Vasu Deva. It establishes a simple solution that can be applied in vari- ous sectors like education, healthcare, and so- cial services. The test results show very good performance in recognizing and responding to gestures, which proves that it can be an effec- tive communication aid for those with hearing impairments. The study also brings out the role of accessible technologies in creating an inclusive and cohesive society.

Keyphrases: CNN, Human Gesture Recognition, Python, computer vision, machine learning

@booklet{EasyChair:15930,
  author    = {Pooja Bhatt and Mohammad Awad Baig and Sai Sri Harsha Injam and Bhanu Prakash Rayapati and Vasudeva Gunturu},
  title     = {Sign Language Interpreter},
  howpublished = {EasyChair Preprint 15930},
  year      = {EasyChair, 2025}}