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Research on lip recognition algorithm based on MobileNet + attention-GRU.

Yuanyao Lu1, Kexin Li1

  • 1School of Information, North China University of Technology, Beijing 100144, China.

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|January 19, 2023
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Summary

This study introduces a deep learning lip recognition system to aid the hearing impaired in speech correction. The system uses advanced AI to analyze lip movements, improving pronunciation and communication for users.

Keywords:
GRUMobileNetattention mechanismdeep learninglip recognition

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Area of Science:

  • Artificial Intelligence
  • Computer Vision
  • Human-Computer Interaction

Background:

  • Lip recognition technology is advancing with deep learning and AI, offering potential in computer vision and human-machine interaction.
  • A key application is aiding the hearing impaired in social interactions and pronunciation through automatic lip recognition.
  • Current research prioritizes algorithms and computational performance, with limited focus on practical applications.

Purpose of the Study:

  • To design and develop a deep learning-based lip recognition application system for speech correction in the hearing impaired.
  • To lay the groundwork for widespread implementation of automatic lip recognition technology.
  • To create a system that assists hearing-impaired individuals in learning and correcting pronunciation through mouth shape analysis.

Main Methods:

  • Utilized MobileNet for robust spatial feature extraction from lip images.
  • Employed a gated recurrent unit (GRU) network for 2D image and temporal feature extraction.
  • Integrated an attention mechanism with the GRU network to enhance recognition rates.

Main Results:

  • The developed deep learning model demonstrated robust and fault-tolerant feature extraction.
  • Experimental results validated the effectiveness of the attention-enhanced GRU network for lip recognition.
  • A lip similarity matching system was successfully constructed to aid pronunciation correction.

Conclusions:

  • The developed deep learning-based lip recognition system is highly feasible and effective for speech correction in the hearing impaired.
  • This research contributes a practical application of AI in medical healthcare and rehabilitation.
  • The system provides a valuable tool for improving communication and learning for individuals with hearing impairments.