Ar-MUSA / README.md
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---
task_categories:
- text-classification
- audio-classification
- image-classification
language:
- ar
size_categories:
- 1K<n<10K
license: afl-3.0
tags:
- multimodal
- sentiment
- analysis
- arabic
- Ar-MUSA
---
# Data Directory Structure
The `Ar-MUSA` directory contains annotated datasets organized by batches and annotation teams. Each batch is labeled with a number, and the annotation team is indicated by a letter. The structure is as follows:
```
Ar-MUSA
├── Annotation 1a
│ ├── frames # Contains the extracted frames for each record
│ ├── audios # Contains the corresponding audio files
│ ├── transcripts # Contains the transcripts of the audio files
│ └── annotations.csv # CSV file with annotations for each record
├── Annotation 1b
│ ├── frames # Contains the extracted frames for each record
│ ├── audios # Contains the corresponding audio files
│ ├── transcripts # Contains the transcripts of the audio files
│ └── annotations.csv # CSV file with annotations for each record
└── Annotation 2a
├── frames # Contains the extracted frames for each record
├── audios # Contains the corresponding audio files
├── transcripts # Contains the transcripts of the audio files
└── annotations.csv # CSV file with annotations for each record
```
### Explanation:
- **Annotation Batches (1a, 1b, 2a, etc.)**:
- The number represents the batch number (e.g., Batch 1, Batch 2).
- The letter indicates the team responsible for the annotation (e.g., Team A, Team B).
### Contents of Each Batch:
1. **frames/**: A folder containing extracted video frames for each record.
2. **audios/**: A folder with the corresponding audio files for the annotated records.
3. **transcripts/**: A folder containing the text transcripts of the audio files.
4. **annotations.csv**: A CSV file that includes the annotations for each record, detailing sentiment labels, sarcasm markers, and other relevant metadata.
### License
The AR-MUSA dataset is licensed under the Academic Free License 3.0 (afl-3.0) and is provided for research purposes only. Any use of this dataset must comply with the terms of this license.
### Citation
If you use the AR-MUSA dataset in your research, please cite the following paper:
@article{khaled2025ar,
title={AR-MUSA: a multimodal benchmark dataset and evaluation framework for Arabic sentiment analysis},
author={Khaled, S. and Ragab, M. E. and Helmy, A. K. and Medhat, W. and Mohamed, E. H.},
journal={International Journal of Intelligent Engineering and Systems},
volume={18},
number={4},
pages={30-44},
year={2025},
doi={10.22266/ijies2025.0531.03}
}