---
dataset_info:
  features:
  - name: chunk_id
    dtype: string
  - name: audio
    dtype:
      audio:
        sampling_rate: 16000
  - name: transcript_text
    dtype: string
  - name: duration
    dtype: float32
  - name: original_video_id
    dtype: string
  splits:
  - name: train
    num_bytes: 21512714764.745
    num_examples: 33599
  download_size: 21214510227
  dataset_size: 21512714764.745
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
language:
- ar
license: other
tags:
- arabic
- speech
- asr
- tts
- egyptian-arabic
- audio
pretty_name: Mostafa Mahmoud Arabic Speech Dataset
task_categories:
- text-to-speech
- automatic-speech-recognition
---


# Mostafa Mahmoud Arabic Speech Dataset

## Dataset Summary

The Mostafa Mahmoud Arabic Speech Dataset is a large-scale Arabic speech corpus containing approximately **187 hours of speech recordings** and corresponding transcripts derived from publicly available lectures, interviews, television appearances, and talks by Dr. Mostafa Mahmoud.

The dataset was created to support Arabic speech technology research and development, including:

* Automatic Speech Recognition (ASR)
* Text-to-Speech (TTS)
* Speech Foundation Models
* Audio-Text Alignment
* Speaker Adaptation
* Arabic Language Technology Research

Transcriptions were generated and curated by the dataset creator using an AI-assisted transcription pipeline and additional quality-control procedures.

With 187 hours of speech from a single speaker, the dataset is particularly suitable for:

* High-quality Arabic TTS voice cloning
* Speaker adaptation and speaker representation learning
* Long-form ASR training
* Foundation model pretraining and fine-tuning
* Research on Arabic speech and narration styles

## Dataset Statistics

| Metric                | Value                        |
| --------------------- | ---------------------------- |
| Language              | Arabic                       |
| Speaker               | Dr. Mostafa Mahmoud          |
| Total Audio Duration  | ~187 Hours                   |
| Number of Speakers    | 1                            |
| Tasks                 | ASR, TTS                     |
| Transcript Generation | AI-assisted, creator-curated |
| Format                | Audio + Text                 |



يحتفظ المنشئون الأصليون والقنوات المالكة بكافة الحقوق، ولا يتم ادعاء أي ملكية للملفات الصوتية الأصلية أو المحتوى الصوتي الأساسي.