MohamedGomaa30/Masri-Elders
Masri Elders Speech-to-Text Dataset Dataset Description This dataset contains Egyptian Arabic (Masri) speech recordings from elderly speakers, paired with their transcriptions. It is designed to help improve Automatic Speech Recognition (ASR) models for this specific dialect and demographic, which is often underrepresented in standard datasets. Language: Egyptian Arabic (Masri) Demographic: Elders Sampling Rate: 16kHz (Mono) Format: WAV audio + Text transcripts… See the full description on the dataset page: https://huggingface.co/datasets/MohamedGomaa30/Masri-Elders.
Masri Elders Speech-to-Text Dataset
Dataset Description
This dataset contains Egyptian Arabic (Masri) speech recordings from elderly speakers, paired with their transcriptions. It is designed to help improve Automatic Speech Recognition (ASR) models for this specific dialect and demographic, which is often underrepresented in standard datasets.
- Language: Egyptian Arabic (Masri)
- Demographic: Elders
- Sampling Rate: 16kHz (Mono)
- Format: WAV audio + Text transcripts
Dataset Structure
The dataset follows a standard audio dataset format:
- `wavs/`: Directory containing the audio segments.
- `metadata.csv`: A CSV file mapping audio files to transcripts.
Metadata Schema
Usage
You can load this dataset directly using the Hugging Face datasets library:
from datasets import load_dataset
dataset = load_dataset("MohamedGomaa30/Masri-Elders")
# Listen to a sample
print(dataset['train'][0])Source Code
The pipeline used to generate this dataset is open-source and available on GitHub: [GitHub Repository: Mohamed-Gomaa30/Masri-Elders-Dataset](https://github.com/Mohamed-Gomaa30/Masri-Elders-Dataset)
License
This dataset is released under the MIT License.
