AI-Generated Alternative Text Suggestions for Images in Moodle: Enhancing Web Accessibility for Visually Impaired Users

March 2, 2024March 2, 2024 Discipline: Computer science

The enclosed documents pertain to the proposal and the desired structure of the thesis, which focuses on developing a plugin for the Moodle forum system that utilizes a large language model. This Thesis focuses on comparing newest pretrained Image to Text Models

  • UForm (unum-cloud)
  • InstructBLIP-Vicuna13B
  • CLIP-Interrogator
  • Img2Prompt
  • LLaMA-13B
  • LLaMA-7B
  • BLIP-2
  • OpenAI GPT-4-Vision-Preview
Some of the Evaluation Metrics could be 
  • SQA (Semantic Quality Assessment)
  • MME (Multimodal Embedding Evaluation)
  • MMBench (Multimodal Benchmarking)
  • Average Size (of the model)
  • Caption Length (generated text length)
  • CLIPScore (for measuring the relevance of the generated text to the image)
  • RefCLIPScore (reference-based CLIPScore for contextual accuracy)
  • VQAv2 (Visual Question Answering version 2 performance)
  • Token Speed (generation speed measured in tokens per second)
The Thesis requirses a working Plugin for Moodle Image to Text writen in Php/Javascript to generate Alternative Text in the Field “image_altentry” for Atto and TinyMCE

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