Indian Sign Language recognition using LSTM and mediapipe

Recognition of Indian Sign Language (ISL) is critical in overcoming communication gaps among the hearing-impaired and the hearing world. To comprehend the nuanced motions of ISL, multiple approaches such as Long Short-Term Memory (LSTM) and Recurrent Neural Networks (RNN) are used in this difficult endeavor. Hand recognition algorithms recognise sign gestures and use convex hull techniques for precise tracking by utilising technologies such as MediaPipe. Furthermore, preprocessing techniques such as unsharp mask filtering improve image quality, which aids in correct recognition. The system uses Pyttsx3 for text-to-speech functionality to enable low latency communication.The incorporation of these cutting-edge technologies enables the system to transform ISL gestures into textual form and vice versa, encouraging inclusion and enabling the hearing-impaired community to fully participate in discussions and information exchange.