Dumb Recognizer

Each individual utilize language to communicate with others. The listening to disable individuals likewise utilize language to communicate among themselves. Sign language is basically utilized by deaf or dumb people to communicate with each other, developed by deaf or dumb communities. The intension

Project Title

Dumb Recognizer

Project Area of Specialization

Artificial Intelligence

Project Summary

Each individual utilize language to communicate with others. The listening to disable individuals likewise utilize language to communicate among themselves. Sign language is basically utilized by deaf or dumb people to communicate with each other, developed by deaf or dumb communities. The intension of the sign language translation system is to translate the normal sign language into speech and to make easy contact with the dumb people. There is serious challenge for the hearing impaired person trying to communicate with normal people. This is because not every single typical people can comprehend their gesture based communication. The greater part of ordinary individuals has not been taught about the sign language. As communication is imperative, this issues inevitably makes a limitation for the impaired individuals to correspond with the normal. Therefore, a sign language translator must be developed to tackle those issues. Since those people who cannot speak are usually deprived of normal communication with other people, they have to rely on an interpreter or some visual communication. Now the interpreter cannot be available always, so this project can help eliminate the dependency on the interpreter

Provide access to those people who cannot speak(mutism) to communicate with the normal people.

This technology can play an important role in various defence and security issues where in people have to communicate through sign language

Provide access to mutism people to speak in seminars and to deliver his/her thoughts because the person's in front of them can easily understand.

The system can be extended to incorporate the knowledge of facial expressions and body language too so that there is a complete understanding of the context and tone of the input

speech.

For the development of our project the software methodology that we would be using will the “prototype approach”. we have chosen this methodology as it will allow us to add more functions and modules to the project later if needed. Therefore the prototype model provide us with flexibility in our project for adding more functionality later and with the use of it we will also not need to rep eat the whole process of adding function during its development.

The idea is to translate audio to text, then from text to sign. audio to text is a mature language technology we are going to use artificial intelligence and machine language.

This project is based on converting the audio signals received to text using speech to text API and then using the semantic of natural language processing to breakdown the text into smaller understandable pieces which requires.

Machine learning as a part, data sets of predefined sign language are used as the input so that the software can use artificial intelligence to display the converted audio into sign

Natural language processing is the application of computational techniques to the analysis and synthesis of natural language and speech.

Project Objectives

• To develop gesture recognizing system that can recognize sign gesture of Pakistan Sign Language and translate it into audio and text.so it become easy for normal person to understand the sign language of deaf or dumb persons.
• To design an algorithm that can translate hand gestures into readable text and speech.
• This technology can play an important role in various defence and security issues where in people have to communicate through sign language.
• Learning of latest technology by interfacing sensors, accelerometers with the microcontroller at the detection unit. Interfacing the base station microcontroller with the LCD and speaker.
• Explore the sign language for those who find difficulty in speaking as well as for normal person’s to understand dumb person.
•  Our objective is to design a solution that is intuitive and the architecture of the system is quiet simple make it easy accessible to all kind of people whether they are from technical or non-technical background.

Project Implementation Method

 Image processing:

The image processing technique using the camera to capture the image/video . Analysis the data with static images and recognize the image using algorithms and produce sentences in the display, vision based sign language recognition system mainly follows the algorithms are Hidden Markov Mode Artificial Neural Networks and Sum of Absolute Difference (SAD) Algorithm use to extract the image and eliminate the unwanted background noise. The main drawback of vision based sign language recognition system image acquisition process have many environmental apprehensions such as the place of the camera ,background condition and lightning sensitivity. Camera place to focus the spot that capture maximum achievable hand movements, higher resolution camera take up more computation time and occupy more memory space. User always need camera forever and cannot implement in public place.

 Data Glove:(Our Search Space):

Another research approach is a sign language recognition system using a data glove. user need to wear glove consist of flex sensor and motion tracker. Data are directly obtained from each sensor depends upon finger flexures and computer analysis sensor data with static data to produce sentences. Its using neural network to improve the performance of the system. The main advantage of this approach less computational time and fast response in real time applications. Its portable device and cost of the device also low. Another approach using a portable Accelerometer (ACC) and Surface Electro Myogram (sEMG) sensors using to measure the hand gesture. ACC used to capture movement information of hand and Arms. EMG sensor placed on the hand, its generate different sign gesture.

Sensor output signals are fed to the computer process to recognize the hand gesture and produce speech/text.

Benefits of the Project

• Since those people who cannot speak are usually deprived of normal communication with other people, they have to rely on an interpreter or some visual communication. Now the interpreter cannot be available always, so this project can help eliminate the dependency on the interpreter
• Provide access to those people who cannot speak(mutism) to communicate with the normal people.
• This technology can play an important role in various defence and security issues where in people have to communicate through sign language
• Provide access to mutism people to speak in seminars and to deliver his/her thoughts because the person's in front of them can easily understand.
• The system can be extended to incorporate the knowledge of facial expressions and body language too so that there is a complete understanding of the context and tone of the input speech
• This technology can help dumb person to participate in seminars, meeting, conferences and deliver their message.
• This system can be extended in future to cover the whole sign language of dumb community and used for various educational and job purposes.

 

Technical Details of Final Deliverable

1-Webcame

2-Glove(with sensors and resistors)

3-Arduinio

Final Deliverable of the Project

HW/SW integrated system

Core Industry

IT

Other Industries

IT

Core Technology

Artificial Intelligence(AI)

Other Technologies

Artificial Intelligence(AI)

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

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