Sign Language Recognition Using Machine Learning

Some individuals face challenges with speaking or hearing, and they rely on sign language to communicate. Sign language enables those who cannot speak or hear to express themselves without using words. Communicating with those who are hard of hearing can be challenging for regular individuals, as understanding the hand gestures of deaf and mute individuals can be difficult. Therefore, there is a need for technologies that can recognize different signs and notify the general public. However, since these regular people have trouble understanding what they're saying, skilled sign language interpreters are required for medical, legal, educational, and training sessions. The need for these services has grown during the previous several years. Additional services, such video remote human interpreters that operate over high-speed Internet connections, have been launched. These services offer a user-friendly sign language interpretation service that has significant limits but can beneficial. To address this challenge, we can use artificial intelligence to analyze a person's hand movements and identify their fingers. By implementing a real-time vision-based system, we can offer a practical solution to enhance communication for individuals using sign language afterwards classifying the sign and providing a label about the recognized sign using a machine learning method called the Convolutional Neural Network method.