File size: 2,299 Bytes
2cdfdec
8237772
 
2cdfdec
 
 
8237772
2101025
7e43056
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2cdfdec
 
8237772
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
---
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 πŸš€
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 πŸ› οΈ
- **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