Conversion of Sign Language to Text and Speech using Machine Learning Techniques
There are 1.5 billion people according to WHO (World Health Organization) who live with hearing loss so to address their ‘disabling’ hearing loss. The American Sign Language(ASL) is most popular languages used by deaf people to communicate with each other. There is constant scientific research and existing models to make accurate predictions. Deep learning model trained on American Sign Language which will take actions in the form of ASL as input and translates into text.
Deaf Sign Language To Text Convertor Project using Machine Learning, In this project there is two modules, first module works for Sign language to Audio Convertor and second option is for Audio to Text Convertor.
1. Let’s explore first module, when the user click on first button it will open laptop front camera and user can show the gesture using hand sign and it will convert into text. model will predict text according to person hand gesture. User have to place hand in particular boundary box and with black or plain background so model can predict with better accuracy. Esc button for close the camera frame.
2. Second module is to convert audio to text convertor, user have to provide input of audio and once user click on start speech button then system will take input of voice through mic and if user click on convert button then machine learning model will convert voice into text. It will gave output in two languages English and kannada.
Sign Language Detection using Machine Learning
Software Requirements :-
- Coding Language : Python
- Implementation: Software Framework.
- Operating system : Windows 10 / 11.
- Graphical User Interface : Tkinter
Hardware Requirement:-
- Input Devices : Keyboard, Mouse.
- System : Pentium i3 Processor.
- Hard Disk : 500 GB.
- RAM : 4 GB.
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