license:cc-by-sa-4.0 size_categories:1K<n<10K format:csv modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
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license: cc-by-sa-4.0
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ShihhiNMT is a parallel dataset composed of 8,000 sentences in Modern Standard Arabic and Shihhi Arabic. It is intended to be used for fine-tuning Neural Machine Translation models and Large Language Models for Shihhi Arabic.

Shihhi Arabic is a dialect of Arabic spoken in the United Arab Emirates and Oman, particularly in the Musandam Peninsula.

This dataset was created and curated using a proprietary method developed by XRI Global which ensures coverage of a conceptual space when doing data collection. This method was developed in order to create the fastest and most affordable way to collect pristine in-domain data for low-resource languages optimized for fine-tuning language models.

The contributors gave proper consent, were hired by a local agency, and were compensated fairly.

For data collection, we utilized our mobile data collection app, Echonet, and our custom translation management system.

The domain is somewhat generalized and the dataset is most effective at literary and narrative texts. It is less capable in other domains such as technical, scientific, or colloquial.

If you are interested in creating ideal datasets for new languages, reach out to us at contact@xriglobal.ai