Sayan Deb Sarkar
2023
HaVQA: A Dataset for Visual Question Answering and Multimodal Research in Hausa Language
Shantipriya Parida
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Idris Abdulmumin
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Shamsuddeen Hassan Muhammad
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Aneesh Bose
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Guneet Singh Kohli
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Ibrahim Said Ahmad
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Ketan Kotwal
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Sayan Deb Sarkar
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Ondřej Bojar
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Habeebah Kakudi
Findings of the Association for Computational Linguistics: ACL 2023
This paper presents “HaVQA”, the first multimodal dataset for visual question answering (VQA) tasks in the Hausa language. The dataset was created by manually translating 6,022 English question-answer pairs, which are associated with 1,555 unique images from the Visual Genome dataset. As a result, the dataset provides 12,044 gold standard English-Hausa parallel sentences that were translated in a fashion that guarantees their semantic match with the corresponding visual information. We conducted several baseline experiments on the dataset, including visual question answering, visual question elicitation, text-only and multimodal machine translation.
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