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Sign Language Recognition for Arabic Alphabets Using Transfer Learning Technique.

Mohammed Zakariah1,2, Yousef Ajmi Alotaibi1,2, Deepika Koundal3

  • 1College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia.

Computational Intelligence and Neuroscience
|May 2, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces an AI system for Arabic Sign Language (ASL) interpretation, translating hand gestures into text. The EfficientNetB4 model achieved 95% accuracy, offering a cost-effective communication solution for the deaf community.

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Human-Computer Interaction

Background:

  • Sign language is the primary communication method for deaf and mute individuals.
  • Reliance on human interpreters is costly and inaccessible for many.
  • A significant communication barrier exists between the deaf community and the general population.

Purpose of the Study:

  • To develop an automated system for Arabic Sign Language (ASL) interpretation.
  • To provide a cost-effective and accessible communication tool for deaf and mute individuals.
  • To convert visual ASL hand gestures into textual information.

Main Methods:

  • Utilized a dataset of 54,049 Arabic Sign Language images.
  • Applied various image preprocessing and data augmentation techniques.
  • Experimented with pre-trained models, focusing on EfficientNetB4 for its robust architecture.

Main Results:

  • The EfficientNetB4 model demonstrated superior performance compared to lighter architectures.
  • Achieved a training accuracy of 98% and a testing accuracy of 95%.
  • EfficientNetB4's complex architecture was well-suited for the intricate ASL dataset.

Conclusions:

  • The developed AI system effectively interprets Arabic Sign Language with high accuracy.
  • EfficientNetB4 is a suitable model for complex sign language recognition tasks.
  • This technology offers a promising, affordable solution to bridge communication gaps for the deaf community.