mabahboh/ArVoice-Undiacritized

ArVoice (+ text_undiacritized)

A derivative of MBZUAI/ArVoice with one added column, text_undiacritized: the transcription transcripts with diacritics removed. Audio and original transcripts are unchanged.

Unofficial derivative. Not produced, endorsed, or maintained by MBZUAI or the ArVoice authors. All credit for the recordings, synthesis, transcripts and curation belongs to them.

Attribution (CC BY 4.0)

Original work	ArVoice: A Multi-Speaker Dataset for Arabic Speech Synthesis
Creators	Hawau Toyin, Rufael Marew, Humaid Alblooshi, Samar M. Magdy, Hanan Aldarmaki (MBZUAI)
Source	MBZUAI/ArVoice, commit 98ade23b24851329f0a528dac4edc0f453f71121, DOI 10.57967/hf/5635
Source license	CC BY 4.0
This derivative	Prepared by mabahboh on 2026-09-28, released under CC BY 4.0

Changes from the source

• Added text_undiacritized next to transcription: Unicode NFC, then every Arabic combining mark removed (harakat, tanween, shadda, sukun, superscript alef, madda, Quranic marks) except hamza above/below; tatweel removed, alef wasla (ٱ) written as alef (ا). Hamza letters (أ إ ؤ ئ آ) are kept.
• Nothing else: audio columns, transcription, speaker ids, splits and row order are identical to the source.
• Configs mirror the source (Human_3, Synthetic, and default = their union, stored once).

Config	Split	Rows
Human_3	train	907
Human_3	test	100
Synthetic	train	20,056
Synthetic	test	2,048

Notes for users

• Speaker ids such as ar-XA-Standard-A name voices of a commercial TTS service used to create the synthetic part. Besides this dataset's license, check that provider's terms before using the synthetic audio in a commercial product.
• Provided as is, without warranties of any kind (Section 5 of the license; full text in LICENSE). If you share this data or material derived from it, credit the original ArVoice work and indicate your own changes.

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Original dataset card (verbatim from MBZUAI/ArVoice @ 98ade23b2485)

ArVoice: A Multi-Speaker Dataset for Arabic Speech Synthesis

Hawau Olamide Toyin, Rufael Marew, Humaid Alblooshi, Samar M. Magdy, Hanan Aldarmaki

{hawau.toyin, hanan.aldarmaki}@mbzuai.ac.ae

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.
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.

This repo consists of only Parts (3), ASC subset, and (4) synthetic subset ; to access the main subset, part (1,2), which consists of six professional speakers, please sign this agreement and email it to us.

If you use the dataset or transcriptions provided in Huggingface, place cite the paper.

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},
}