A Framework for the Automatic Generation of Indian Sign Language

Background: The sign language is used by 466 million hearing impaired and deaf people all over the world. It is aimed to develop a system that translates the text into sign language in order to enable individuals with hearing disabilities to better adapt to social life and lead a life without disabilities. Materials and Methods: Sign language dictionary was created by identifying words in American Sign Language (ASL). Sign language animation videos of the words in the prepared dictionary were created. Morphological analysis was done using natural language processing (NLP) algorithms to identify surface forms, suffixes and the roots of words in a particular sentence and to adapt the sentence to ASL. Results: By analyzing the structure of ASL, an algorithm has been developed that converts English text into ASL. As a result of the morphological analysis, the words whose roots are detected and the videos of all the items in the sentence to be translated are pulled from the database and combined and played. Thus, the translation system of the text to ASL was created. Conclusion:It is thought that people with hearing impairment who do not understand what they read can improve the quality of education and life with the text-to-sign translation system.

Sign language is a language which uses visually transmitted sign patterns to convey meaning. It is the combination of hand shapes, orientation and movement of hands, arms or body, and facial expressions. Our System is capable of recognizing sign-language symbols can be used as a means of communication with hard of hearing people and hard speaking people. Our paper proposes a system to help those people to communicate with normal people without sophisticated devices like power, data gloves and coloured finger cap and etc. Instead we are using a camera and microphone as a device to implement the Integrated Two Way ISL (Indian Sign Language) system. The Two Way ISL translation system has two parts, translation of sign language into voice and reverse. The Two Way ISL translation system uses webcam or USB camera to get images or continuous video image (from hard speaking) which can be interpreted by the application. Acquired images are assumed to be translation, scale and rotation invariant. Assuming signer is right angle to the camera. In this process the steps of translation are acquisition of images, binarised, classification, hand shape edge detection and feature extraction. After getting vectors feature extraction state then pattern matching done by comparing existing database. The interpreted symbols (meaning-words) can be translated into text information (Words in English or Tamil). Using text to voice synthesis, text will be converted as a voice output or voices file (to normal person). The GUI application is displaying and sending the message as a text message or voice message to the receiver. The reverse is, getting voice input (from normal person) converted to text then it is matching with database for sign symbol to display (to hard hearing receiver).This system makes deaf/dumb people to communicate easily with normal speaking person. Also in video calling or chatting this application helps the hard speaking and hearing people.

Computers, Materials & Continua, 2022

Communication is a basic need of every human being; by this, they can learn, express their feelings and exchange their ideas, but deaf people cannot listen and speak. For communication, they use various hands gestures, also known as Sign Language (SL), which they learn from special schools. As normal people have not taken SL classes; therefore, they are unable to perform signs of daily routine sentences (e.g., what are the specifications of this mobile phone?). A technological solution can facilitate in overcoming this communication gap by which normal people can communicate with deaf people. This paper presents an architecture for an application named Sign4PSL that translates the sentences to Pakistan Sign Language (PSL) for deaf people with visual representation using virtual signing character. This research aims to develop a generic independent application that is lightweight and reusable on any platform, including web and mobile, with an ability to perform offline text translation. The Sign4PSL relies on a knowledge base that stores both corpus of PSL Words and their coded form in the notation system. Sign4PSL takes English language text as an input, performs the translation to PSL through sign language notation and displays gestures to the user using virtual character. The system is tested on deaf students at a special school. The results have shown that the students were able to understand the story presented to them appropriately.

We report a cross-modal translation system from Hindi strings to Indian Sign Language (ISL) for possible use in the Indian Railways reservation counters. INGIT adopts a semantically mediated formulaic framework for Hindi-ISL mapping. An in-depth investigation into the structure of ISL forms the groundwork for INGIT. Some representational and mapping issues concerning cross-modal translation are identified and an implementation design is evolved. We adopt the Construction Grammar approach for handling formulaic inputs in terms of a construction lexicon with single constituents as well as larger phrases, with direct semantic mappings at each level. We present results based on a small corpus collected at a railway counter, for which translations were validated from native ISL signers. The work builds upon a semantic module worked out for Hindi and ISL.

This paper discusses the development of an automatic machine translation (MT) system for translating spoken language text into signed languages (SLs). The motivation for our work is the improvement of accessibility to airport information announcements for D/deaf and hard of hearing people. This paper demonstrates the involvement of Deaf colleagues and members of the D/deaf community in Ireland in three areas of our research: the choice of a domain for automatic translation that has a practical use for the D/deaf community; the human translation of English text into Irish Sign Language (ISL) as well as advice on ISL grammar and linguistics; and the importance of native ISL signers as manual evaluators of our translated output.

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

Sign language display is the software of converting the text/speech to animated sign language to meet the demands of the special needs population. The goal of this is to make the communication A more comfortable and to improve both health and productivity .As technology has improved, the usage of computer systems has increased, which means we can implement better ways to meet the needs that can impact the health of special needs population. So, this project could help people improve their communication. Thus, they improve their mental health .With the help of Blender, Python, SQL, and NLP, We have tried to design a process to detect text and subsequently the live speech , which can converted to animated sign language in real time. For the entire process, I used Blender for animation and video processing and SQL and NLP to determine the different words and text to by training the dataset and for text to animation conversion .Therefore, this project could to meet the needs of many people .The number of different countries use different sign language even same countries that are multilingual use a different system which meets the social and cultural standards of their countries. As such there is a wide disparity in many countries for digital sign language But, Software such as our could be helpful to bridge the gap between such discrepancies and be useful not just for acting as a tool for communication but also as tool use to teach. In conclusion , it is very cost effective and widely applicable .

In recent years data-driven methods of machine translation (MT) have overtaken rule-based approaches as the predominant means of automatically translating between languages. A pre-requisite for such an approach is a parallel corpus of the source and target languages. Technological developments in sign language (SL) capturing, analysis and processing tools now mean that SL corpora are becoming increasingly available. With transcription and language analysis tools being mainly designed and used for linguistic purposes, we describe the process of creating a multimedia parallel corpus specifically for the purposes of English to Irish Sign Language (ISL) MT. As part of our larger project on localisation, our research is focussed on developing assistive technology for patients with limited English in the domain of healthcare. Focussing on the first point of contact a patient has with a GP's office, the medical secretary, we sought to develop a corpus from the dialogue between the two parties when scheduling an appointment. Throughout the development process we have created one parallel corpus in six different modalities from this initial dialogue. In this paper we discuss the multi-stage process of the development of this parallel corpus as individual and interdependent entities, both for our own MT purposes and their usefulness in the wider MT and SL research domains.

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

This project's primary purpose is to bridge the gap between deaf and hearing persons, which will benefit those with hearing impairments who employ a simple and effective way of sign language. Sign language is a visual language used by the deaf community. It employs body language, hand gestures, and facial expressions. Indian Sign Language is one of the most significant and commonly utilised modes of communication for individuals with speech and hearing difficulties. This web application facilitates communication for deaf and speech-impaired individuals. The primary focus of these new web application and natural language processing technologies is the conversion of spoken or written language into sign language. In this web application, users can record their speech using a microphone or text as input utilising NLP-based speech recognition. If the video is missing from the database, the word is spit out and the associated video is displayed. This technique has made communicating with deaf individuals simple and practical.

International Journal of Computer Applications, 2015

A person who is hearing impaired or mute is not able to compete or work with a normal person because of lack of proper communication between the two. This paper presents the development of an application which will enable a hassle free communication between physically disabled person and normal person. The application is responsible for the conversion of hand gestures into a meaningful sentence which can be read out by a normal person. In this approach, gestures based on Indian sign language are used. The major steps associated with the application are gesture recognition and natural language processing as most important module in the paper proposed. The current work can be used as an interface to communicate with speech impaired and normal person. Thus, it will bridge the gap between speech impaired and normal people by capturing sign processing it recognizing it & presenting output as meaningful sentence.

1994

The sign languages used by deaf communities around the world represent a linguistic challenge that natural language researchers have only recently begun to take up. Zardoz is a system which tackles the cross-modal machine-translation problem, translating speech and text into animated sign language. Native sign !languages, such as ISL (Ireland), BSL (Britain) and ASL (U.S.A.) have evolved in deaf communities as natural methods of gestural communication. These languages differ from English, not only in modality, but in grammatical structure, exploiting the dimensions of space as well as time. This paper presents an architectural overview of Zardoz, and describes the methods employed to analyse the verbal input and generate the corresponding signed output.