Akash Kamble - Academia.edu (original) (raw)
Related Authors
Universidade Estadual Paulista "Júlio de Mesquita Filho"
Uploads
Papers by Akash Kamble
Energy, environment, and sustainability, 2024
International Journal for Research in Applied Science and Engineering Technology
Sign language is a form of communication that uses hand sign and gestures to convey meaning. we p... more Sign language is a form of communication that uses hand sign and gestures to convey meaning. we present a new approach to converting sign language into text format. Our system is designed to enable deaf and mute people to communicate with others in a more accessible and convenient way. The proposed method uses computer vision and deep learning methods to recognize hand gestures and translate them into appropriate text. The system was built using a combination of key point detection using MediaPipe, data pre-processing, label, feature generation and LSTM neural network training. This work has the potential to significantly improve communication for deaf and dumb individuals and reduce the barriers to communication with the rest of the world. The system uses key point detection algorithms such as MediaPipe to identify hand gestures and a Lstm model to translate them into corresponding text output. The data collected from the sign language is pre-processed and then used to train an LSTM neural network to accurately recognize gestures and produce text output. This method of conversion not only helps deaf and hard of hearing individuals communicate with the hearing population, but also serves as an assistive tool for individuals who are trying to learn sign language. Overall, the proposed solution has the potential to greatly improve communication and reduce barriers for deaf and hard of hearing individuals
Energy, environment, and sustainability, 2024
International Journal for Research in Applied Science and Engineering Technology
Sign language is a form of communication that uses hand sign and gestures to convey meaning. we p... more Sign language is a form of communication that uses hand sign and gestures to convey meaning. we present a new approach to converting sign language into text format. Our system is designed to enable deaf and mute people to communicate with others in a more accessible and convenient way. The proposed method uses computer vision and deep learning methods to recognize hand gestures and translate them into appropriate text. The system was built using a combination of key point detection using MediaPipe, data pre-processing, label, feature generation and LSTM neural network training. This work has the potential to significantly improve communication for deaf and dumb individuals and reduce the barriers to communication with the rest of the world. The system uses key point detection algorithms such as MediaPipe to identify hand gestures and a Lstm model to translate them into corresponding text output. The data collected from the sign language is pre-processed and then used to train an LSTM neural network to accurately recognize gestures and produce text output. This method of conversion not only helps deaf and hard of hearing individuals communicate with the hearing population, but also serves as an assistive tool for individuals who are trying to learn sign language. Overall, the proposed solution has the potential to greatly improve communication and reduce barriers for deaf and hard of hearing individuals