CV-18 NER: Augmented Common Voice for Named Entity Recognition from Arabic Speech
Paper • 2604.02209 • Published
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CV-18 NER
CV-18 NER is the first publicly available dataset for Named Entity Recognition (NER) from Arabic speech. It was created by augmenting the Arabic Common Voice 18 corpus with manual NER annotations following the fine-grained Wojood schema, which covers 21 entity types.
The dataset provides a benchmark for evaluating both pipeline systems (ASR + text NER) and end-to-end speech NER models. It is particularly valuable for research in low-resource settings and morphologically complex languages like Arabic.
More information can be found in the paper: CV-18 NER: Augmented Common Voice for Named Entity Recognition from Arabic Speech.
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