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Datasets:
EMINES
/
Tamazight-Speech-to-Arabic-Text

Tasks:
Automatic Speech Recognition
Modalities:
Audio
Text
Formats:
parquet
Languages:
Arabic
Standard Moroccan Tamazight
Size:
10K - 100K
Tags:
speech
tamazight
arabic
speech-to-text
low-resource
north-africa
Libraries:
Datasets
Dask
License:
Dataset card Data Studio Files
xet
Community
1
Tamazight-Speech-to-Arabic-Text
File size: 3,851 Bytes 
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---
language:
- ar
- zgh
license: apache-2.0
task_categories:
- automatic-speech-recognition
pretty_name: Tamazight-Arabic Speech Recognition Dataset
size_categories:
- 10K<n<100K
tags:
- speech
- tamazight
- arabic
- speech-to-text
- low-resource
- north-africa
---

# Tamazight-Arabic Speech Recognition Dataset

## Overview

This is the EMINES organization-hosted version of the [Tamazight-Arabic Speech Recognition Dataset](https://huggingface.co/datasets/SoufianeDahimi/Tamazight-ASR-Dataset-v2), synchronized with the original dataset. It contains ~15.5 hours of Tamazight speech (Tachelhit dialect) paired with Arabic transcriptions, designed for developing ASR and translation systems.

### Quick Start

```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("EMINES/Tamazight-Speech-to-Arabic-Text")

# Example usage
for example in dataset["train"]:
    audio = example["audio"]
    text = example["text"]
    metadata = example["metadata"]
```

## Dataset Description

The dataset contains speech segments in Tamazight (Tachelhit dialect) paired with Modern Standard Arabic transcriptions. It serves as a foundation for:
- Speech recognition systems for Tamazight
- Speech-to-text translation models
- Linguistic research and language preservation

### Dataset Statistics

- **Total Examples:** 20,344 audio segments
- **Training Set:** 18,309 examples (~8.9GB)
- **Test Set:** 2,035 examples (~992MB)
- **Total Duration:** ~15.5 hours
- **Audio Format:** WAV
- **Text Format:** Arabic script

### Data Fields

```python
{
    'audio': {
        'path': str,        # Path to the audio file
        'array': np.array,  # The audio signal
        'sampling_rate': int # Sampling rate of the audio
    },
    'text': str,           # Arabic transcription
    'metadata': {
        'duration': float,  # Duration in seconds
        'start_time': float, # Start time in original video
        'end_time': float,  # End time in original video
        'language': str,    # Language code
        'source': str      # Source video identifier
    }
}
```

## Community & Development

This is an actively growing community project. We welcome contributions in:

1. **Data**
   - New audio-text pairs (Tachelhit)
   - Other Tamazight dialects (Tarifit, Central Atlas)
   - Transcription validation

2. **Technical Improvements**
   - Open-source subtitle extraction solutions
   - Pipeline optimizations
   - Preprocessing techniques

The source code for the data processing pipeline will be available soon!

### Future Development

The dataset is expanding to include:
- Additional Tamazight dialects
- Improved data processing tools
- Community-contributed enhancements

## Limitations and Biases

- Current focus on Tachelhit dialect
- Source material limited to movie content
- Variable audio quality
- Potential OCR-related transcription errors

## Additional Information

### Citation

If you use this dataset, please cite both the organization version and the original dataset:

```bibtex
@dataset{tamazight_asr_2024,
  author       = {Contributors},
  title        = {Tamazight-Arabic Speech Recognition Dataset},
  year         = {2025},
  publisher    = {Hugging Face},
  howpublished = {\url{https://huggingface.co/datasets/EMINES/Tamazight-Speech-to-Arabic-Text} \url{https://huggingface.co/datasets/SoufianeDahimi/Tamazight-ASR-Dataset-v2}}
}
```

### License

Apache 2.0

### Links

- [Original Dataset](https://huggingface.co/datasets/SoufianeDahimi/Tamazight-ASR-Dataset-v2)
- [GitHub Repository](link-to-github-repo) <!-- Add when available -->
- [Issue Tracker](link-to-issues) <!-- Add when available -->

### Acknowledgments

This dataset was initially created by [Soufiane Dahimi](https://huggingface.co/SoufianeDahimi) and is now maintained by the community under the EMINES organization umbrella.