Sign Language Recognition Project with Source Code
Sign Language Detection and Sentence Suggestion leverage neural networks to interpret and understand sign language gestures. This application translates sign language into text or speech, facilitating communication between individuals with hearing impairments and those who do not know sign language. The neural networks’ proficiency in recognizing diverse sign language gestures ensures accurate translation and promotes inclusivity in communication.
Sign Language Recognition using Machine Learning, In this project it works on Sign to Text Conversion Project, ML model is trained on large dataset of images of word (i.e., call, good, hello, house, no, ok, etc.). User have to show the exact sign of alphabets, digits and word from hand gesture in front of camera to detect the type of sign it is. Machine Learning model is trained on YOLO Algorithm to detect the hand signs.
Real-Time Sign Language Detection and Recognition in Different Language
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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