Deaf and Dumb Gesture Recognition System

2016

Communication between normal and handicapped person such as deaf people, dumb people, and blind people has always been a challenging task. It has been observed that they find it really difficult at times to interact with normal people with their gestures, as only a very few of those are recognized by most people. Since people with hearing impairment or deaf people cannot talk like normal people so they have to depend on some sort of visual communication in most of the time. Sign Language is the primary means of communication in the deaf and dumb community. As like any other language it has also got grammar and vocabulary but uses visual modality for exchanging information. The importance of sign language is emphasized by the growing public approval and funds for international project. Interesting technologies are being developed for speech recognition but no real commercial product for sign recognition is actually there in the current market. So, to take this field of research to an...

Bioscience Biotechnology Research Communications, 2020

Primary mode of communication is speech by which information can transfer. But hearing-impaired people are not able to communicate with the world. In this paper, low cost prototype model is developed to bridge communication gap for disable people like deaf, dumb and blind. Dump person uses sign language and blind person uses voice, both gives output in text and audio form. System uses atmega-32 as microcontroller, video recording module and flex sensor for developing communication between deaf and dumb with Blind person. For those persons who bothered to express their feelings due to their lack of ability, this device will helpful for them.

International Journal of Advance Research Ideas and Innovations in Technology

The sensible adaption of interface solutions for visually impaired and blind folks is proscribed by simplicity and usefulness in practical situations. Totally different solutions focus upon speech or keyboard interfaces, that don't seem to be economical or clear in everyday environments. As a straightforward and sensible thanks to bringing home the bacon human-computer-interaction, during this paper hand gesture recognition was accustomed to facilitate the reduction of hardware parts. In addition, a qualitative user study was performed to match the learning curves of various subjects with and while not previous data of gesture recognition devices, decoding the readings from a sensitive surface by machine learning algorithms. The user study was created victimization well-known machine learning algorithms applied to recognize symbols from the graffiti handwriting system and therefore the woodhen data processing computer code for scrutiny individual machine learning approaches.

IRJET, 2022

Communicating with people is a fundamental form of interaction, and being able to do so with people who have hearing impairments has proven to be a significant challenge. As a result, we are using Sign language as a critical tool for bridging the communication gap between hearing and deaf people. Communicating through sign language is difficult, and people with hearing impairments struggle to share their feelings and opinions with people who do not speak that language. To address this issue, we require a versatile and robust product. We proposed a system that aims to translate hand signals into their corresponding words as accurately as possible using data collected and another research. This can be accomplished through the use of various machine learning algorithms and techniques for classifying data into words. For our proposed system, we are using the Convolutional neural networks (CNN) algorithm. The process entails being able to capture multiple images of various hand gestures using a web cam in this analysis, and the system being able to predict and display the corresponding letters/words of the captured images of hand gestures that have previously been trained with Audio. Once an image is captured, it goes through a series of procedures that include computer vision techniques such as gray-scale conversion, mask operation, and dilation. The main goal and purpose of this project will be to remove the barrier between deaf and dumb people and normal people.

— Sign language recognition is one of the most growing fields of research today and it is the most natural way of communication for the people with hearing problems. A hand gesture recognition system can provide an opportunity for deaf persons to communicate with normal people without the need of an interpreter or intermediate. We are going to build a systems and methods for the automatic recognition of Marathi sign language. Through that we are providing teaching classes for the purpose of training the deaf sign user in Marathi. The system does require hand to be properly aligned to the camera and does not need any special colour markers, glove or wearable sensors. A large set of samples has been used in proposed system to recognize isolated words from the standard Marathi sign language which are taken in front of camera by different deaf sign user. In our proposed system, we intend to recognize some very basic elements of sign language and to translate them to text and vice versa. Keywords— Sign Language, Deaf Sign User, Sign and Text Database, Canny's Algorithm.

—Communications between deaf-mute and a normal person have always been a challenging task. This paper reviews a different methods adopted to reduce barrier of communication by developing an assistive device for deaf-mute persons. The advancement in embedded systems, provides a space to design and develop a sign language translator system to assist the dumb people, there exist a number of assistant tools. The main objective is to develop a real time embedded device for physically challenged to aid their communication in effective means.

Applied and Computational Engineering

This work concentrates on the device, which helps as a translation system for translating sign gestures into text. The disabled people, in particular, hearing and speech impaired people, are facing difficulties in society. Communication of disabled people becomes worse as the majority of ordinary people do not understand it. These disabled people face difficulty communicating with others; some have many problems communicating with others in sign language. It causes the communication gap between them where impaired people cannot share their views and skills with others. We headed to facilitate communication between the disabled people and the "Tamil sign language translator to solve this problem." Here, gestures are translated to Tamil language to find a localized solution. It processes 31 Tamil alphabets, 12 Vowels, 18 Consonants, and 1 Aayudha Ezhuthu. It is 32 combinations with five fingers points either up or down and mapped to decimal numbers. Here in this process, we ...

2021

The Dynamics of the world changed after the invention of electricity and followed by the invention of the internet. These inventions drastically changed the standard of living. The technology prospered in all sectors with time. People started finding comfort in automation. Thus, we propose a smart communication system to enhance the standard of living for the deaf and mute. This system uses sign recognition based on dynamic hand gesture recognition techniques in real-time scenarios. Computer Vision-based techniques were used for image analysis. The captured video of the hand is converted to Hue, Saturation, Value (HSV) color space for processing and then segmentation was done based on skin pixels. Contour Extraction is used in parallel to get more accurate results. Then the classification of gestures was done by Support Vector Machine(SVM) Classifier. The respective message is displayed through a mobile application ’SAHARA’.

International Journal of Advanced Trends in Computer Science and Engineering , 2022

Hand gesture is one of the styles used in sign language for non-verbal communication. It's most generally used by deaf & dumb people who have hearing or speech problems to communicate among themselves or with normal people. Plathora sign language systems had been developed by numerous makers around the world but they're neither flexible nor cost-effective for the end druggies. Hence, it's a software which presents a system prototype that's suitable to automatically recognize sign language to help deaf and dumb people to communicate more effectively with each other or normal people. Dumb people are generally deprived of normal communication with other people in the society, also normal people find it hard to understand and communicate with them. These people have to depend on an interpreter or on some kind of visual communication. An interpreter won't be always available and visual communication is substantially delicate to understand. As a normal person is ignorant of the grammar or meaning of numerous gestures that are part of a sign language, it's primarily limited to their families and/ or deaf and dumb community.

International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2022

Sign Language is globally used by more than 70 million impaired people to communicate and is characterized by fast, highly articulate motion of hand gesture which is difficult for verbal speakers to understand. This limitation combined with the lack of knowledge about sign language by verbal speakers creates a separation where both parties are unable to effectively communicate, to overcome this limitation we propose a new method for sign language recognition using OpenCV (A python library) which is used for pre-processing images and extracting different skin toned hands from the background. In this method hand gesture are used to make signs which are detected by YOLOv5 algorithm for object detection which is the fastest algorithm till date while Convolutional-Neural-Networks (CNN) are used for training gesture and to classify the images, and further we proposed a system which translates speech into sign language so that the words of the verbal speaker can be transmitted to the deaf/mute. This automated system first detects speech using the JavaScript Web-Speech API and converts it into text because the recognized text is processed using the Natural Language Toolkit and aligns token text with the sign language library (sign language videos) videos according to well-known text and finally shows a compiled output which is displayed through avatar animation for a deaf / dumb person. The proposed system has various advantages like Portability, User-friendly Interface and Voice Module. The software is also very cost-effective which only needs a laptop camera or webcam and hand gesture, system accuracy is compared to high-quality methods and is found to be the best.