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Dataset Summary

This corpus is a dataset that contains 1,000 hours of speech sampled at 16~kHz and crawled from over 700 YouTube channels. MASC is multi-regional, multi-genre, and multi-dialect dataset that is intended to advance the research and development of Arabic speech technology with the special emphasis on Arabic speech recognition

Supported Tasks and Leaderboards

[More Information Needed]


Multi-dialect Arabic

Dataset Structure

Data Instances

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Data Fields


  • speech
  • sampling_rate
  • target_text (label)

Data Splits


  • train: 100
  • test: 40

Dataset Creation

Curation Rationale

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Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

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Annotation process

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Who are the annotators?

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Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

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Other Known Limitations

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Additional Information

Note: this is a small development set for testing.

Dataset Curators

[More Information Needed]

Licensing Information

CC 4.0

Citation Information

[More Information Needed]


Mohammad Al-Fetyani, Muhammad Al-Barham, Gheith Abandah, Adham Alsharkawi, Maha Dawas, August 18, 2021, "MASC: Massive Arabic Speech Corpus", IEEE Dataport, doi:

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