Sign Language to Text using Deep Learning

Developed a deep learning system for recognizing dynamic sign language gestures and converting them into English words.

The project involved preprocessing video data and extracting sequences of frames to capture the temporal patterns of different gestures. A BiLSTM-based deep learning model was used to process the sequential data and recognize the corresponding sign language words.

The project included data preprocessing, training and testing, model evaluation, and comparison of multiple machine learning and deep learning approaches to identify an effective solution for sign language recognition.