Speaking System for Dumb People Using Hand Gestures

Speech is the easiest way for communication in the world. It becomes difficult for speech impaired people to communicate with normal people as they use sign language for communication. When a speech-impaired person communicates with normal person, the gap between speech impaired and normal masses is too much to fill. The gesture recognition can be done in two ways, Image processing based and sensor-based. The "Smart Gloves for Deaf and Dumb People" project seeks to provide practical solution for individuals with speech and hearing impairments, enabling them to communicate more easily with others. The project utilizes an ESP32 micro-controller, a versatile and powerful platform, to control and process the data from touch sensors integrated into the gloves. These touch sensors are designed to recognize specific hand gestures made by the user, with each gesture corresponding to a particular rerecorded voice message. The APR33A3 voice record and audio playback board plays a critical role in this project, as it stores and outputs audio files linked to the detected gestures. By using the board's 8-channel capability, a range of messages can be stored, providing a variety of responses for different gestures. The system is aimed at enhancing communication for individuals who are deaf or mute by translating sign language or hand gestures into audible speech, thereby improving interaction with others and enhancing social inclusion. This innovative approach combines hardware, software, and audio technology to create a user-friendly tool that empowers individuals with disabilities to express themselves in a more natural and effective manner.

Publication Details

Journal
Journal on Electronic and Automation Engineering
Published
2025-06-07
DOI
https://doi.org/10.46632/jeae/4/2/39
Primary Topic
Hand Gesture Recognition Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Speaking System for Dumb People Using Hand Gestures

Journal on Electronic and Automation Engineering
Hand Gesture Recognition Systems
article

Speaking System for Dumb People Using Hand Gestures

article en

Abstract

Speech is the easiest way for communication in the world. It becomes difficult for speech impaired people to communicate with normal people as they use sign language for communication. When a speech-impaired person communicates with normal person, the gap between speech impaired and normal masses is too much to fill. The gesture recognition can be done in two ways, Image processing based and sensor-based. The "Smart Gloves for Deaf and Dumb People" project seeks to provide practical solution for individuals with speech and hearing impairments, enabling them to communicate more easily with others. The project utilizes an ESP32 micro-controller, a versatile and powerful platform, to control and process the data from touch sensors integrated into the gloves. These touch sensors are designed to recognize specific hand gestures made by the user, with each gesture corresponding to a particular rerecorded voice message. The APR33A3 voice record and audio playback board plays a critical role in this project, as it stores and outputs audio files linked to the detected gestures. By using the board's 8-channel capability, a range of messages can be stored, providing a variety of responses for different gestures. The system is aimed at enhancing communication for individuals who are deaf or mute by translating sign language or hand gestures into audible speech, thereby improving interaction with others and enhancing social inclusion. This innovative approach combines hardware, software, and audio technology to create a user-friendly tool that empowers individuals with disabilities to express themselves in a more natural and effective manner.

Journal on Electronic and Automation EngineeringVol. 4(2 June 2025)
Openalex Percentile: Top 88%
Hand Gesture Recognition Systems
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Speaking System for Dumb People Using Hand Gestures · Journal on Electronic and Automation Engineering (2025) | TGRS Research Map | TGRS