Implementation of Converting Indian Sign Language into Indian Language Using IoT-based Machine Learning Algorithms
D. Sivabalaselvamani, D. Selvakarthi, L. Rahunathan, S. Gokulprasath, D. Jagane, S Logeshwar · 2024
A language is a basic tool used to share information, ideas, and feelings with people. Communication plays a major role in people’s life. To communicate with more people, common languages like Tamil, English, etc., are used by people. However, sign language was utilized by the dumb and deaf to communicate. Deaf and dumb people can find it difficult to communicate with normal people because they don’t know the sign language they use to communicate. This is becoming a barrier between normal people and deaf and dumb people. To solve this problem can create a machine learning model to detect sign language and translate it into normal language. This helps disabled people to communicate with normal people without any difficulties. The available solutions are either not real-time or only moderately accurate. On both metrics, this system produces good performance. It can recognize some ISL motions and hand poses. A camera is used to collect sign language, which is then analyzed using a machine learning model to predict the sign and translate it into text. The sign images are collected by using a camera and the images are labeled by their sign. After that, images are used to train and test the model. Using this method can reduce the difficulties. Because no additional hardware, like gloves or the Microsoft Kinect sensor, is needed, it is user-friendly. Only a camera is used to capture and detect sign language. With a small amount of data, this approach predicts sign language effectively.