Hand Gesture Recognition for speech-impaired people because they have their own sign language but normal people don’t know the sign language which is used for intercommunication between speech impaired people.
The main problem we are focusing is the inability of differently abled people(speech-impaired) to communicate with normal people or other differently abled people, because they have their own sign language but normal people don’t know the sign language which is used for intercommunication between mute people. This system will be useful to solve this problem and help them to make their interaction easily with the people. They can communicate hassle-free by using this device & with the help of our app, we converted gesture pattern into text to Speech. Now, we are here with the combined Hardware and Software solution which is called “speech system using hand gesture ”, after analysing some problems. And, try to make the next generation Support Device for differently abled people.(speech-impaired) The hand gestures are one of the typical methods used in sign language. It is very difficult for the differently abled people to communicate with the world. This project presents a solution that will not only automatically recognise the hand gestures but will also convert it into speech and text output so that impaired person can easily communicate with normal people. On the whole, the solution aims to provide aid to those in need thus ensuring social relevance. The people can easily communicate with each other. The user-friendly nature of the system ensure that people can use it without any difficulty and complexity. The application is cost efficient and eliminates the usage of expensive technology.
There is a Hardware project which consists of a Hand Gesture Recognition. Hand Gesture Recognition for speech-impaired people because they have their own sign language but normal people don’t know the sign language which is used for intercommunication between speech impaired people. As computer innovation keeps on developing, the requirement for characteristic correspondence amongst people and machines additionally increments. In spite of the fact that our cell phones influence utilisation of the touch to screen innovation, it is not sufficiently shabby to be actualised in work area frameworks. In spite of the fact that the mouse is exceptionally valuable for gadget control, it could be badly arranged to use for physically disabled individuals and individuals who are not familiar with utilising the mouse for connection. The strategy proposed in this paper makes utilisation of a webcam through which hand gestures gave by the user are captured and identified accordingly. Hand gestures have boundless applications. In this investigation, we apply it to a system to make a straightforward easy to understand interaction interface. In our app, we will use specifications like Text to Speech (for Speech-impaired people with bluetooth connectivity).
In the Hardware of this project, Hand Gesture Recognition for “Speech-impaired People” using Arduino, Bluetooth HC 05, LDR Sensors & our app, through we convert gesture pattern into text to Speech. Then, Text to Speech with bluetooth connection and Speech to Text were implemented with our skills. The system makes use of a fingers motion reading system equipped with LDR sensors along with a Bluetooth module (HC-05) which can transmit data to the mobile, with the help of app it is spoken out and display on screen simultaneously. This system is powered by a battery powered circuitry to run it. Arduino is used for processing the data and operating the system. The system consists of around 16 stored messages like “ Help”, “Danger”, “Hungry” and so on that help, mute people convey basic messages. The system reads person fingers motions for different variations of hand movement. The Arduino constantly receives input sensor values and then processes it. Now it searches for matching messages for the set of sensor values with a specific pattern. Once it is found in memory this messages is retrieved and is spoken out using mobile app. Thus we have a fully functional smart speaking system to help mute people communicate with regular people using a simple wearable system.
Working of Hand Gesture recognition is so efficiently and accurately. Also, make a this device very cheap around 13 USD. ( There some sensors in market whose cost around 30 USD each then for four fingers 120 USD with other components additional cost also) And, converted Text to Speech & Speech to Text successfully.
In terms of enhancing the project, we can introduce some sensors with the help of Gyrometer sensor in hand gesture, we can increase the limits of signs means available for different sentences instead of common words. In terms of marketing the product, we would like to initially target differently abled people centre of our region. The application can be integrated with other mobile and IoT devices to improve user interaction and make the system more robust. The accuracy of the program can be further improvised by using neural networks. An alternate stress could be put on the use of the application in the fields of medicines, governance etc. A genuine blend of various technologies in mentioned fields could make way for power tools and applications which will serve the community around the world. Finally, the use can be further designed to make more accessible to the consumers. The whole point of making the solution as a commercially viable product for the users is to help the impaired community around the world.
The practical adaption of the interface solution for speech impaired people is limited by simplicity and usability in practical scenarios. As an easy and practical way to achieve human-computer- interaction, in this solution hand gesture to speech and text conversion has been used to facilitate the reduction of hardware components. On the whole, the solution aims to provide aid to those in need thus ensuring social relevance. The people can easily communicate with each other. The user-friendly nature of the system ensure that people can use it without any difficulty and complexity. The application is cost efficient and eliminates the usage of expensive technology.
-> Varnit Goswami
-> Divya Maheshwari