LERMO: A Novel Web Game for AI-Enhanced Sign Language Recognition

Authors

  • Adilson Medronha Pontifical Catholic University of Rio Grande do Sul
  • Luís Lima Pontifical Catholic University of Rio Grande do Sul
  • Janaína Claudio Pontifical Catholic University of Rio Grande do Sul
  • Lucas Kupssinskü Pontifical Catholic University of Rio Grande do Sul
  • Rodrigo C. Barros Pontifical Catholic University of Rio Grande do Sul

DOI:

https://doi.org/10.1609/aaai.v38i21.30384

Keywords:

Sign Language Recognition, LIBRAS, Accessibility, AI Education, Machine Learning, Computer Vision

Abstract

Sign language is a visual and gestural communication system used by deaf and hearing-impaired people. Despite numerous deep learning methods proposed for automatic interpretation, a gap persists in developing applications that effectively utilize these models for assisting sign language studies and inclusion. We introduce LERMO (https://lermo.app/), a web game merging machine learning and gamification to enhance sign language fingerspelling. Inspired by Wordle™, LERMO offers an interactive word-guessing game where users can play using a video camera. We create a new dataset of labeled landmark fingerspelling and design our model to ensure optimal speed and efficiency to run on a web browser. We survey approximately 40 users, which find LERMO user-friendly and innovative. From those, 95% believe LERMO could be used to enhance fingerspelling skills.

Published

2024-03-24

How to Cite

Medronha, A., Lima, L., Claudio, J., Kupssinskü, L., & Barros, R. C. (2024). LERMO: A Novel Web Game for AI-Enhanced Sign Language Recognition. Proceedings of the AAAI Conference on Artificial Intelligence, 38(21), 23352–23359. https://doi.org/10.1609/aaai.v38i21.30384

Issue

Section

EAAI: Mentored Undergraduate Research Challenge: AI for Accessibility in Comm