Auditory Aid for Understanding Images for Visually Impaired Students Using CNN and LSTM

EasyChair Preprint 13897

Abstract

—The world is leading towards an equal experience in learning in all educational environments, it is also a world where visual content dominates the digital landscape. Hence it is our collective responsibility to ensure that no one is left in the shadows of the information age. By utilizing the power of image captioning, we are championing the cause of inclusion, enabling people with visual impairments to navigate the digital world with confidence and ease. This assistive technology is proposed to promote accessibility and inclusion in literature, allowing people with visual impairments to engage with a wide range of written works. We performed various evaluations to demonstrate the effectiveness of this proposed model, demonstrating its potential to improve the reading experience of blind people, thereby promoting independence and accessibility. Through this paper, we propose an innovative approach that aims to develop adaptive assistive technology to enable visually impaired people to access written and visual content. Ways to design a method of creating descriptive text descriptions of images and making it easier for blind people to understand visual content were explored.

Keyphrases: Assistive Technology, CNN, LSTM, image caption

@booklet{EasyChair:13897,
  author    = {Aashna Arun and Apurvanand Sahay},
  title     = {Auditory Aid for Understanding Images for Visually Impaired Students Using CNN and LSTM},
  howpublished = {EasyChair Preprint 13897},
  year      = {EasyChair, 2024}}