Ecuadorian Sign Language Detection in Real Time

The paper introduces a groundbreaking approach to bridge the communication divide between Ecuadorian Sign Language users and non-sign language speakers. It employs technology for real-time translation of sign gestures into written language. The study used a dataset encompassing alphabet letters, numbers, and common phrases in Ecuadorian Sign Language, employing an object localization model to recognize hand movements. Our system splits images into a grid, facilitating efficient detection of multiple signs in one go. When sign language gestures are input via images or videos, the system identifies and reproduces them in an app, facilitating effective communication. The results indicate promising accuracy and real-time responsiveness, offering hope for improved inclusivity in the Ecuadorian deaf community. This research not only empowers the deaf but also promotes wider appreciation of Ecuadorian Sign Language. Future work aims to enhance accuracy, expand vocabulary, and integrate the technology into diverse communication platforms for broader impact.