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A computer vision application that recognizes hand gestures from a webcam and converts sign language alphabets and common words into text and speech in real time.
Problem Statement
People with hearing and speech impairments face communication barriers because few people understand sign language and interpreters are not always available.
Objectives
Collect and label a hand gesture dataset
Extract hand keypoints from video frames
Train a gesture classification model
Convert recognized signs into text and speech
Modules
Hand Tracking
Detects hands and extracts 21 keypoints per frame.
Gesture Classifier
PyTorch model that maps keypoint sequences to letters and words.
Sentence Builder
Combines recognized signs into words with auto-correction.
Output Interface
Displays text on screen and reads it aloud using text-to-speech.
Expected Output
A desktop or web application that shows recognized letters and words on screen as the user signs in front of the camera.
Future Scope
Indian Sign Language sentence level recognition, two-way translation with an avatar, and a mobile version.