Speech or Text to Indian Sign Language Convertor (original) (raw)

A Translator for Indian Sign Language to Text and Speech

International Journal for Research in Applied Science and Engineering Technology IJRASET, 2020

Verbal Communication is the only way using which people have interacted with each other over the years but the case stands different for the disabled. The barrier created between the impaired and the normal people is one of the setbacks of the society. For the impaired people (deaf & mute), sign language is the only way to communicate. In order to help the deaf and mute communicate efficiently with the normal people, an effective solution has been devised. Our aim is to design a system which analyses and recognizes various alphabets from a database of sign images. In order to accomplish this, the application uses various techniques of Image Processing such as segmentation & feature extraction. We use the machine learning technique, Convolutional Neural Network for detection of sign language. We convert the image by cropping the background and keeping only gesture, after that we convert the gesture into black & white scale in png format into 55*60 resolution. This system will help to eradicate the barrier between the deaf-mute & normal people. This system will standardize the Indian Sign Language in India. It will also improve the quality of teaching and learning in deaf and mute institutes. Just as Hindi is recognized as the standard language for conversation throughout India, ISL will be recognized as the standard sign language throughout India. The main aim of this work is serving the mankind that is achieved by providing better teaching and better learning.

Translation System for Sign Language Learning

International journal of scientific research in computer science, engineering and information technology, 2024

Sign language display software converts text/speech to animated sign language to support the special needs population, aiming to enhance communication comfort, health, and productivity. Advancements in technology, particularly computer systems, enable the development of innovative solutions to address the unique needs of individuals with special requirements, potentially enhancing their mental wellbeing. Using Python and NLP, a process has been devised to detect text and live speech, converting it into animated sign language in real-time. Blender is utilized for animation and video processing, while datasets and NLP are employed to train and convert text to animation. This project aims to cater to a diverse range of users across different countries where various sign languages are prevalent. By bridging the gap between linguistic and cultural differences, such software not only facilitates communication but also serves as an educational tool. Overall, it offers a costeffective and widely applicable solution to promote inclusivity and accessibility.

Text to Sign Language Conversion by Using Python and Database of Images and Videos

The aim of this system is to design an independent communication system for a person who is deaf and hard of hearing. This system is used for converting text to sign language. It is the vision-based system. It takes input as alphabets and numerals and converts them into equivalent sign code and displays on a screen. In this system, we are going to used Indian sign language. Sign language is not same for all part of the world. Sign language is defined as the language of deaf and dumb people by using which they are able to express their thoughts. By using sign language they can transmit messages by combining hand shapes and different movement of hands. Sign language has their own alphabets and grammar. By creating a system that converts text to sign code, which is helpful for communication between normal people and hard of hearing the person.

Real Time Translation of Sign Language to Speech and Text

IARJSET, 2021

Creating a desktop application that uses a computer webcam to capture a person signing gestures for Indian Sign Language (ISL) and translate it into corresponding text and speech in real time. The translated sign language gesture will be acquired in text which is further converted into audio. In this manner we are implementing a finger spelling language translator. To enable the detection gestures, we are making use of a Convolution neural network (CNN). A CNN is highly efficient in tackling computer vision problems and is capable of detecting the desired features with high degree of accuracy upon sufficient training. This project is about converting the hand gesture of sign language to voice or text using Machine Learning Techniques and vice versa. In this we are going to capture a real time translation of indian sign language using single and double hand gestures and recognize the words and convert it into text and then to speech. If the person gives speech as input it is first converted to text and then it displays the suitable sign as output and vice versa.

Text Analysis and Speech to Sign Language Translation

2019

American Sign Language is the most widely known sign language. There are more sign languages used as well. The current scenario is that deaf individuals have already learned the language and use it for their daily communication. The only hurdle is that normal person have to learn the sign language In this paper an architecture is proposed based on machine learning. The system is designed in 3 modules speech to text, text to sign and sign to animation. The first module is implemented using a speech recognition API. The second through a machine learning algorithm. The end module consists of a 3D animated avatar. .

A Real-Time Automatic Translation of Text to Sign Language

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.

Conversion of Sign Language to Text

International Journal for Research in Applied Science and Engineering Technology

Sign language is a form of communication that uses hand sign and gestures to convey meaning. we present a new approach to converting sign language into text format. Our system is designed to enable deaf and mute people to communicate with others in a more accessible and convenient way. The proposed method uses computer vision and deep learning methods to recognize hand gestures and translate them into appropriate text. The system was built using a combination of key point detection using MediaPipe, data pre-processing, label, feature generation and LSTM neural network training. This work has the potential to significantly improve communication for deaf and dumb individuals and reduce the barriers to communication with the rest of the world. The system uses key point detection algorithms such as MediaPipe to identify hand gestures and a Lstm model to translate them into corresponding text output. The data collected from the sign language is pre-processed and then used to train an LSTM neural network to accurately recognize gestures and produce text output. This method of conversion not only helps deaf and hard of hearing individuals communicate with the hearing population, but also serves as an assistive tool for individuals who are trying to learn sign language. Overall, the proposed solution has the potential to greatly improve communication and reduce barriers for deaf and hard of hearing individuals

Animation system for Indian Sign Language communication using LOTS notation

2013

This paper presents an application aiding the social integration of the deaf community in India into the mainstream of society. This is achieved by feeding text in English and generating an animated gesture sequence representative of its content. This application consists of three main portions: an interface that allows the user to enter words, a language processing system that converts English text to ISL format and a virtual avatar that acts as an interpreter conveying the information at the interface. These gestures are dynamically animated based on a novel method devised by us in order to map the kinematic data for the corresponding word. The word after translation into ISL will be queried in the database where in lies the notation format for each word. This notation called as LOTS Notation will represent parameters enabling the system to identify features like hand location(L), Hand Orientation (O) in the 3D space, Hand Trajectory movement (T), hand shapes (S) and non-manual components like facial expression. The animation of a sentence fed is thus produced from the sequence of notations which are queued in order of appearance. We are also inserting the movement-epenthesis which is the inter sign transition gesture inorder to avoid jitters in gesturing. More than a million deaf adults and around half a million deaf children in India use the Indian Sign Language (ISL) as a mode of communication. However, this system would serve as an initiative in propelling the Sign Language Communication in the Banking Domain. The low audio dependency in the working domain supports the cause.

Automatic Translation of Real-Time Voice to Indian Sign Language for Deaf and Dumb People

International Journal of Innovative Research in Science, Engineering and Technology (IJIRSET), 2023

Sign language is a universal way of communication for challenged people with speaking and hearing limitations. Multiple mediums are accessible to translate or to acknowledge sign language and convert them to text. However, the text to signing conversion systems has been rarely developed; this is often thanks tothe scarcity of any sign language dictionary. Our projectaims at creating a system that consists of a module that initially transforms voice input to English text and which parses the sentence, then to which Indian sign language grammar rules are applied. This is done by eliminating stop words from the reordered sentence. Indian SignLanguage (ISL) does not sustain the inflections of theword. Hence, stemming is applied to vary over the wordsto their root/ stem class. All words of the sentence are then Checked against the labels in the dictionary containingvideos representing each of the words. The present systems are limited to only straight conversion of wordsinto ISL, whereas the proposed system is innovative, as our system aims to rework these sentences into ISL as pergrammar in the real domain.

Indian Sign Language (ISL) Translation System For Sign Language Learning

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. Our paper proposes a system to help normal people can easily communicate with hard of hearing people. Instead we are using a camera and microphone as a device to implement the Indian Sign Language (ISL) system. The ISL translation system has translation of voice into Indian Sign Language. The ISL translation system uses microphone or USB camera to get images or continuous video image (from normal people) which can be interpreted by the application. Acquired voices are assumed to be translation, scale and rotation invariant. In this process the steps of translation are acquisition of images, binarized, classification, hand shape edge detection and feature extraction. After getting vectors feature extraction state then pattern matching done by comparing existing database. The GUI application is displaying and sending the message to the receiver. This system makes normal people to communicate easily with deaf/dumb person. Also in video calling or chatting this application helps the hard speaking and hearing people.