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| title: Albert Latest 96 | |
| emoji: 🐨 | |
| colorFrom: blue | |
| colorTo: pink | |
| sdk: docker | |
| pinned: false | |
| short_description: AI model to classify accessibility-related bugs. | |
| # Accessibility Bug Prediction Using ALBERT 🐞 | |
| This project leverages the **ALBERT (A Lite BERT)** model to classify software bug reports into two categories: | |
| 1. Accessibility-related bugs. | |
| 2. Non-accessibility bugs. | |
| It also includes a **custom Jira plugin** to integrate the AI model into the bug-tracking workflow, making it easier for development teams to identify and prioritize accessibility issues. | |
| ## Key Features ✨ | |
| - **State-of-the-Art NLP**: Utilizes the ALBERT transformer model, fine-tuned for high accuracy on bug report classification tasks. | |
| - **Custom Dataset**: The model was trained from scratch on a dataset collected by the research team. | |
| - **Jira Plugin Integration**: Seamlessly integrates the classification system into Jira to enhance accessibility compliance workflows. | |
| - **Research Collaboration**: Developed under the guidance of **Professor Wajdi Aljedaani**, a UX and Human-Centered AI researcher. | |
| ## How It Works 🚀 | |
| 1. **Input**: Provide a textual description of a bug report. | |
| 2. **Prediction**: The ALBERT model analyzes the text and classifies the bug as either accessibility-related or not. | |
| 3. **Output**: Use the results directly or integrate them into Jira for workflow optimization. | |
| ## Applications 🛠️ | |
| - **Software Development**: Identify accessibility bugs to ensure compliance with standards like WCAG. | |
| - **Quality Assurance**: Optimize testing and prioritization for accessibility-related issues. | |
| - **Research in UX and AI**: Leverage insights for designing inclusive and accessible systems. | |
| ## Deployment 🌐 | |
| The model is hosted on **Hugging Face Spaces**, providing an interactive and user-friendly web interface. | |
| [Try the Model on Hugging Face](https://huggingface.co/spaces/shivamjadhav/albert_latest_96) | |
| ## About the Research 🤝 | |
| This project was developed as part of a research initiative at **UNT** under **Professor Wajdi Aljedaani**'s guidance. It emphasizes the intersection of AI, UX, and accessibility to drive impactful solutions for software development. | |
| --- | |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |