---
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
dataset_info:
  features:
  - name: audio
    dtype: audio
  - name: transcription
    dtype: string
  splits:
  - name: train
    num_bytes: 6486606662.193651
    num_examples: 8874
  download_size: 5389628614
  dataset_size: 6486606662.193651
---
# Arabic-Diacritized-TTS Dataset

## Overview
The **Arabic-Diacritized-TTS** dataset contains Arabic audio samples and their corresponding text with full diacritization. This dataset is designed to support research in Arabic speech processing, text-to-speech (TTS) synthesis, automatic diacritization, and other natural language processing (NLP) tasks.

## Dataset Contents
- **Audio Samples**: High-quality Arabic speech recordings.
- **Text Transcriptions**: Fully diacritized Arabic text aligned with the audio.

## Data Generation
The dataset was generated using the **TTS Arabic** model from the following repository:

[https://github.com/nipponjo/tts_arabic](https://github.com/nipponjo/tts_arabic)

### About the Model
The **TTS Arabic** model is an advanced text-to-speech system for Arabic, capable of generating high-quality, natural-sounding speech with full diacritization. It is built on deep learning techniques and trained on diverse Arabic text and speech datasets. The model:
- Supports Modern Standard Arabic (MSA).
- Includes proper diacritic placement to enhance pronunciation accuracy.
- Is optimized for high-fidelity and intelligibility in Arabic speech synthesis.

## Usage
This dataset can be used for:
- Training and evaluating Arabic **ASR (Automatic Speech Recognition)** models.
- Enhancing **TTS (Text-to-Speech)** systems with diacritized text.
- Improving **Arabic diacritization** models.
- Conducting **linguistic research** on Arabic phonetics and prosody.

## Citation
If you use this dataset, please cite the source and credit the contributors.

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For any inquiries or contributions, feel free to reach out!