Gesture to Speech Using CNN and Python: A Real-Time System for Sign Language Translation

By: Mani, Dhanus

A system designed to convert hand sign gestures into voice and text using a Python- based Convolutional Neural Network (CNN) model offers a robust solution for bridging communication gaps. This system leverages computer vision techniques to capture hand gestures, which are then processed by a trained CNN model for recognition. The recognized gestures are subsequently converted into textual output and further synthesized into speech using text-to-speech (TTS) libraries. This approach provides a real- time, accessible method for individuals using sign language to communicate with those unfamiliar with it, enhancing inclusivity and understanding.

• Format: Paperback
• Language: English
• ISBN: 9999330266
• ISBN13: 9789999330268
• Release Date: October 2025
• Publisher: Eliva Press
• Length: 68 Pages
• Weight: 0.23 lbs.
• Dimensions: 0.1" x 6.0" x 9.0"