International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 04 | Apr 2023
p-ISSN: 2395-0072
www.irjet.net
Gestures Based Sign Interpretation System using Hand Glove V. Leela Krishna1, P. Sekhar2, P. Gowri Priya Mani3, S. Bala Satya Phani Kumar4 1,2,3,4 Students, Dept. of Electronics & Communication Engineering, R.V.R. & J.C. College of Engineering, Guntur,
Andhra Pradesh, India ---------------------------------------------------------------------***--------------------------------------------------------------------for the future. As the technology advances, we can expect to Abstract – In this article, we introduce a system for
see even more advanced systems that can accurately interpret more complex sign language gestures and provide more sophisticated translations. Ultimately, these devices have the potential to break down the communication barriers that exist between the deaf and hard of hearing and the rest of society, opening up new possibilities for personal and professional relationships.
interpreting sign language that utilizes a glove. People who are unable to speak often communicate using sign language, which can pose a challenge when trying to communicate with those who do not understand it. To address this issue, we propose a glove-based system that utilizes Arduino Uno and flex sensors to translate hand gestures into text and speech. By doing so, we hope to reduce the communication gap between those who use sign language and those who do not, making it easier for people with speech impairments to communicate with others.
The main objective of developing the Sign Language Interpreter was to facilitate communication between the deaf and hearing communities. This is achieved through the use of a sensor-based hand glove that is connected to an Arduino microcontroller, allowing for the translation of hand gestures into text and sound. With this smart glove, communication barriers between communities can be eliminated.
The glove-based sign interpretation system is a promising solution for enabling communication between individuals who use sign language and those who do not. This paper presents a system that uses Arduino Uno and flex sensors to interpret hand gestures and convert them into text and speech. The proposed system has the potential to greatly reduce the communication gap between speech-impaired individuals and those who do not understand sign language. This could revolutionize communication for those who use sign language and help break down barriers to communication.
Individuals with speech disabilities often experience difficulties in communicating with others. The purpose of this device is to enhance their quality of life by converting their gestures into speech, providing a voice for those who are unable to speak. Speech is an important tool for conveying messages, and this project utilizes flex sensors that are attached to the gloves to capture hand movements. The output from these sensors is then sent to the Arduino, where the data is used to display text on an LCD screen and produce speech output through an Android app.
Key Words: Glove-based sign interpretation system, communication, sign language, Arduino Uno, flex sensors, hand gestures, text, speech, machine learning, speech impairment.
1. INTRODUCTION
The main focus of this project is to create a system that can recognize a predefined set of hand gestures, particularly the American Sign Language alphabet, using a data glove as an input device. To achieve this, the system will employ artificial intelligence tools such as artificial neural networks to facilitate interaction between the user and the computer. The system will classify and recognize the hand gestures performed by the user. The ASL alphabet comprises static and dynamic gestures, where static gestures are accomplished by maintaining a hand pose while dynamic gestures involve both hand pose and movement.
A glove-based sign interpretation system is a device that utilizes advanced technology to help people who are deaf or hard of hearing communicate with others who do not understand sign language. This device consists of a special glove equipped with sensors that track the movement of the wearer's hands and fingers, and then translate the gestures into written or spoken language. The system uses machine learning algorithms to recognize and interpret the sign language gestures made by the wearer. It can then convert these gestures into a variety of languages, including English, Spanish, French, and others. This technology has the potential to revolutionize communication for the deaf and hard of hearing, as it enables them to express themselves more effectively and easily with the people around them. Glove-based sign interpretation systems are still in their early stages of development, but they hold immense promise
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