Sign Language Conversion Using Machine Learning
Year: 2025
Type: article
Abstract: The goal of this research is to employ computer vision techniques to construct a system for detecting sign language. For the deaf and hard-of-hearing people, sign language is an essential form of communication. This technology attempts to close the communication gap by automatically identifying and translating sign language motions. converting them to text. The suggested system takes pictures of a person signing with a camera, then analyzes the picture frames in order to identify and identify hand gestures. The system makes use of algorithms to categorize the identified hand motions and associate them with the appropriate sign language words or phrases. KEY WORDS: Sign language, Detection, Recognition, Computer vision, Image classification, Performance evaluation, Accuracy
DOI: 10.55041/ijsrem42072
Author: Dr.M. SENGALIAPPAN
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4408150034