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Robust Identification System for Spanish Sign Language Based on Three-Dimensional Frame Information.

Jesús Galván-Ruiz1, Carlos M Travieso-González1,2, Alejandro Pinan-Roescher1

  • 1IDeTIC, Universidad de Las Palmas de G.C. (ULPGC), 35017 Las Palmas de Gran Canaria, Spain.

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|January 8, 2023
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Summary
This summary is machine-generated.

This study developed a Spanish Sign Language (SSL) transcription tool using a Leap Motion sensor. The system achieved 95.17% accuracy in recognizing dynamic words, aiding communication for individuals with hearing impairments.

Keywords:
Spanish sign languagedynamic time warpinggesture recognitionpattern recognition

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Human-Computer Interaction

Background:

  • Hearing disorders affect a significant portion of the global population, posing challenges to oral communication.
  • Technological advancements are driving the development of assistive tools for individuals with communication disabilities.
  • Spanish Sign Language (SSL) transcription is an area of active research aimed at improving daily communication for the deaf community.

Purpose of the Study:

  • To design and evaluate a system for transcribing Spanish Sign Language (SSL).
  • To leverage motion-sensing technology for real-time sign language recognition.
  • To enhance communication accessibility for individuals with hearing impairments through technological solutions.

Main Methods:

  • Utilized a Leap Motion volumetric sensor for capturing 3D hand movements.
  • Recorded a dataset of 176 dynamic Spanish Sign Language words performed by a hearing-impaired individual.
  • Applied Dynamic Time Warping (DTW) algorithm for sample comparison and prediction.

Main Results:

  • The developed system achieved a prediction accuracy of 95.17% for dynamic Spanish Sign Language words.
  • The Leap Motion sensor effectively captured the nuances of hand gestures in three dimensions.
  • Dynamic Time Warping proved effective in handling variations in signing speed and style.

Conclusions:

  • The proposed technique demonstrates a high accuracy in transcribing Spanish Sign Language, offering a promising assistive communication tool.
  • This research highlights the potential of motion-sensing technology in developing effective sign language recognition systems.
  • The findings contribute to the broader goal of improving digital inclusion and communication accessibility for people with hearing disorders.