MBZUAI/ArVoice

<h2 align="center"> <b>ArVoice: A Multi-Speaker Dataset for Arabic Speech Synthesis</b> </h2> <p align="center"> Hawau Olamide Toyin, Rufael Marew, Humaid Alblooshi, Samar M. Magdy, Hanan Aldarmaki </p> <p align="center"> {hawau.toyin, hanan.aldarmaki}@mbzuai.ac.ae </p>

<div style="font-size: 16px; text-align: justify;"> <p>ArVoice is a multi-speaker Modern Standard Arabic (MSA) speech corpus with fully diacritized transcriptions, intended for multi-speaker speech synthesis, and can be useful for other tasks such as speech-based diacritic restoration, voice conversion, and deepfake detection. <br> ArVoice comprises: (1) professionally recorded audio by 2 male and 2 female voice artists from diacritized transcripts, (2) professionally recorded audio by 1 male and 1 female voice artists from undiacritized transcripts, (3) a modified subset of the Arabic Speech Corpus, and (4) synthesized speech using commercial TTS systems. The complete corpus consists of a total of 83.52 hours of speech across 11 voices; around 10 hours consist of human voices from 7 speakers. <br> <br> <strong> This repo consists of only Parts (3), ASC subset, and (4) synthetic subset </strong>; to access the main subset, part (1,2), which consists of six professional speakers, <a href="https://huggingface.co/datasets/MBZUAI/ArVoice/resolve/main/ArVoice%20DUA.pdf"> please sign this agreement</a> and email it to us. <br><br> If you use the dataset or transcriptions provided in Huggingface, <u>place cite the paper</u>. </p> </div>

Usage Example

df = load_dataset("MBZUAI/ArVoice", "Human_3")  #data_dir options: Human_3, Synthetic,
print(df)

DatasetDict({
    train: Dataset({
        features: ['original_wav', 'normalized_wav', 'speaker_id', 'transcription'],
        num_rows: 907
    })
    test: Dataset({
        features: ['original_wav', 'normalized_wav', 'speaker_id', 'transcription'],
        num_rows: 100
    })
})

Data Statistics | Type | Part | Gender | Speaker Origin | Duration (hrs) | Text Source | |-----------|-----------------|------------|----------------|----------------|------------------------------| | Human | ArVoice Part 1 | M | Egypt | 1.17 | Tashkeela | | | | F | Jordan | 1.45 | | | | | M | Egypt | 1.58 | | | | | F | Morocco | 1.23 | | | | ArVoice Part 2 | M | Palestine | 0.93 | Khaleej | | | | F | Egypt | 0.93 | | | | ArVoice Part 3 | M | Syria | 2.69 | ASC | | Synthetic | ArVoice Part 4 | 2×M, 2×F | - | 73.5 | Tashkeela, Khaleej, ASC |

License: https://creativecommons.org/licenses/by/4.0/

Citation

@inproceedings{toyin25_interspeech,
  title     = {{ArVoice: A Multi-Speaker Dataset for Arabic Speech Synthesis}},
  author    = {Hawau Toyin and Rufael Marew and Humaid Alblooshi and Samar M. Magdy and Hanan Aldarmaki},
  year      = {2025},
  booktitle = {{Interspeech 2025}},
  pages     = {4808--4812},
  doi       = {10.21437/Interspeech.2025-1550},
  issn      = {2958-1796},
}