Gesture Talk -Bridging Silence with Words

Gesture Talk is a real-time sign language-to-text conversion to create a communication environment for the deaf and able-bodied, with a touch of inclusivity across many other domains. The whole idea is to further develop a cheap and efficient solution to translate American Sign Language (ASL) gestures into text without the necessity for an interpreter. The process uses convolutional neural networks (CNNs) with a dual-layer classification algorithm, applying Gaussian blur and adaptive thresholding on the pre-processed webcam video frames and incorporating an auto-correct feature to enhance word prediction. The system was trained and tested on a labeled ASL gestures dataset prepared out of pre-processed 128×128 grayscale images obtained from RGB video inputs. Gesture Talk achieves recognition of 98.0% accuracy for ASL gestures, which surpasses many existing systems, and provides a user-friendly interface supporting all platforms, enabling deployment on desktops, mobiles, and web applications for much greater accessibility for deaf individuals.

Authors

Publication Details

Published
2025-06-03
DOI
https://doi.org/10.38124/ijisrt/25may1721
Primary Topic
Hearing Impairment and Communication
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Gesture Talk -Bridging Silence with Words

Vijay Kumar, Vishal Bansal, Mekhala, Adnan Shoeb
Hearing Impairment and Communication
article

Gesture Talk -Bridging Silence with Words

Vijay Kumar, Vishal Bansal, Mekhala, Adnan Shoeb
article en

Abstract

Gesture Talk is a real-time sign language-to-text conversion to create a communication environment for the deaf and able-bodied, with a touch of inclusivity across many other domains. The whole idea is to further develop a cheap and efficient solution to translate American Sign Language (ASL) gestures into text without the necessity for an interpreter. The process uses convolutional neural networks (CNNs) with a dual-layer classification algorithm, applying Gaussian blur and adaptive thresholding on the pre-processed webcam video frames and incorporating an auto-correct feature to enhance word prediction. The system was trained and tested on a labeled ASL gestures dataset prepared out of pre-processed 128×128 grayscale images obtained from RGB video inputs. Gesture Talk achieves recognition of 98.0% accuracy for ASL gestures, which surpasses many existing systems, and provides a user-friendly interface supporting all platforms, enabling deployment on desktops, mobiles, and web applications for much greater accessibility for deaf individuals.

Openalex Percentile: Top 88%
Hearing Impairment and Communication
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Gesture Talk -Bridging Silence with Words — Vijay Kumar, Vishal Bansal, et al. · (2025) | TGRS Research Map | TGRS