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April 24, 2026Disability and Rehabilitation Assistive Technology

An intelligent emotion recognition system for people with disabilities using stacked supervised autoencoder and brown-bear optimization strategy

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Authors

AAAbdulrhman M. AlshareefKAKhaled H. AlyoubiAAAisha Alsobhi

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Overview

Advanced emotion recognition system aids individuals with disabilities, suggesting significant improvements in communication.

Key Points

  • The study aims to enhance textual emotion recognition to improve communication for individuals with disabilities.
  • Utilizes LBBOWE-ETER method combining word embedding and deep learning techniques.
  • Implements stacked supervised autoencoder for classification and brown-bear optimization for hyperparameter tuning.
  • Involves multiple levels of text pre-processing to transform raw text data for analysis.
  • Achieved an impressive accuracy rate of 98.95% in emotion detection from text.
  • Demonstrated significant performance improvements over existing models.
  • Showed that deep learning techniques effectively enhance emotion recognition capabilities.

Cite This Study

Alshareef et al. (2026) studied this question.

synapsesocial.com/papers/69eb084f553a5433e34b3595https://doi.org/10.1080/17483107.2026.2653077
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Enhancing Textual Emotion Recognition to Aid People with Disabilities Using Brown-Bear Optimization with Stacked Supervised Autoencoder Model2025
  2. 2Enhancing Textual Emotion Recognition to Aid People with Disabilities Using Brown-Bear Optimization with Stacked Supervised Autoencoder Model2025
  3. 3Textual emotion recognition to improve real-time communication of disabled people in sustainable environments using an ensemble deep learning approach2025
  4. 4Integration of corpus linguistics and deep learning techniques for enhanced semantic-driven emotion detection on textual data2025
  5. 5Mathematical modelling of attention-guided deep learning for real-time text emotion recognition in assistive interaction systems for disabled persons2026