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ismailelsayedeltanja/Egyptian-dialect-8k

Egyptian Dialect Speech Dataset (8k) Dataset Description This dataset contains around 8,000 cleaned speech samples in the Egyptian Arabic dialect. It is optimized for speech recognition (ASR), text-to-speech (TTS), and audio processing tasks tailored specifically for Egyptian dialect applications. Primary Language: Egyptian Arabic (ar-EG) Total Samples: ~8,000 audio clips with corresponding text transcriptions. Source: Cleaned and processed from… See the full description on the dataset page: https://huggingface.co/datasets/ismailelsayedeltanja/Egyptian-dialect-8k.

sourceHugging Facec-udaupdated 2mo agoView on Hugging Face
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Dataset Card

language:

  • —ar license: mit task_categories:
  • —automatic-speech-recognition
  • —text-to-speech
  • —audio-classification tags:
  • —arabic
  • —egyptian-dialect
  • —audio
  • —speech size_categories:
  • —1K<n<10K ---

Egyptian Dialect Speech Dataset (8k)

Dataset Description

This dataset contains around 8,000 cleaned speech samples in the Egyptian Arabic dialect. It is optimized for speech recognition (ASR), text-to-speech (TTS), and audio processing tasks tailored specifically for Egyptian dialect applications.

  • —Primary Language: Egyptian Arabic (ar-EG)
  • —Total Samples: ~8,000 audio clips with corresponding text transcriptions.
  • —Source: Cleaned and processed from oddadmix/da7ee7_sep_cleaned-8k.

Quick Start & Usage

Using the datasets library (Recommended)

You can load this dataset with a single line of code using Hugging Face's datasets library:

python
from datasets import load_dataset

# Load the full dataset

import pandas as pd
from datasets import load_dataset, Audio
from IPython.display import display, HTML, Audio as AudioPlayer
OUTPUT_DIR = "/gdrive/MyDrive/TTS-Spark"
dataset = load_dataset("ismailelsayedeltanja/Egyptian-dialect-8k", split="train")
dataset = dataset.cast_column("audio", Audio(sampling_rate=16000))

dataset = dataset.filter(
    lambda x: bool(x.get("text")) and x.get("audio") is not None)

shuffled_dataset = dataset.shuffle(seed=101)
dataset = shuffled_dataset.take(430)
print(f"Data_: \n {dataset}")


display(HTML("<h2 style='color: #4f46e5; font-family: sans-serif; text-align: right;'> Showing_Sample_from_Raw_data  </h2>"))

html_style = """
<style>
    .audio-table {
        border-collapse: separate;border-spacing: 0;margin: 15px 0;font-size: 1em;
        font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;width: 100%;
        direction: rtl;text-align: right;box-shadow: 0 4px 12px rgba(79, 70, 229, 0.12);
        border-radius: 12px;overflow: hidden;border: 1px solid #e0e7ff;
    }
    .audio-table th {
        background: linear-gradient(135deg, #6366f1 0%, #4f46e5 100%);color: #ffffff;
        padding: 14px 18px;font-weight: 600;letter-spacing: 0.5px;
    }
    .audio-table td {padding: 12px 18px;border-bottom: 1px solid #f1f5f9;color: #1e293b;
        background-color: #ffffff;
    }
    .audio-table tr:hover td {background-color: #f5f3ff;color: #4338ca;
    }
    .sample-tag {background-color: #e0e7ff;color: #3730a3;
        padding: 4px 10px;border-radius: 6px;font-weight: bold;
    }
</style>
"""

display(HTML(html_style))

for i in range(1):
    sample = dataset[i]
    text = sample["text"]
    audio_data = sample["audio"]["array"]
    sr = sample["audio"]["sampling_rate"]

    display(HTML(f"""
    <table class="audio-table">
        <tr>
            <th style="width: 15%;">Sample</th>
            <th style="width: 85%;">Texe</th>
        </tr>
        <tr>
            <td><span class="sample-tag">#{i+1}</span></td>
            <td style="font-size: 1.05em; font-weight: 500;">{text}</td>
        </tr>
    </table>
    """))

    display(AudioPlayer(audio_data, rate=sr))

##  Stream the Dataset (Without Downloading Entirely)

from datasets import load_dataset

# Stream dataset
dataset = load_dataset("ismailelsayedeltanja/Egyptian-dialect-8k", streaming=True)

for sample in dataset['train']:
    print(sample['text'])  # Replace 'text' with the actual text column name if different
    break

##  Data Structure
Each entry in the dataset typically contains:

audio: Audio object containing array (waveform), path, and sampling_rate.

text (or transcription): The corresponding text script in Egyptian Arabic.

##  Citation & Acknowledgments

If you use this dataset in your research or project, please credit the original source:

Source repository: oddadmix/da7ee7_sep_cleaned-8k

Re-uploaded and formatted by: @ismailelsayedeltanja