@inproceedings{parida-etal-2025-ovqa,
    title = "{OVQA}: A Dataset for Visual Question Answering and Multimodal Research in {O}dia Language",
    author = "Parida, Shantipriya  and
      Sahoo, Shashikanta  and
      Sekhar, Sambit  and
      Sahoo, Kalyanamalini  and
      Kotwal, Ketan  and
      Khosla, Sonal  and
      Dash, Satya Ranjan  and
      Bose, Aneesh  and
      Kohli, Guneet Singh  and
      Lenka, Smruti Smita  and
      Bojar, Ond{\v{r}}ej",
    editor = "Weerasinghe, Ruvan  and
      Anuradha, Isuri  and
      Sumanathilaka, Deshan",
    booktitle = "Proceedings of the First Workshop on Natural Language Processing for Indo-Aryan and Dravidian Languages",
    month = jan,
    year = "2025",
    address = "Abu Dhabi",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2025.indonlp-1.7/",
    pages = "58--66",
    abstract = "This paper introduces OVQA, the first multimodal dataset designed for visual question-answering (VQA), visual question elicitation (VQE), and multimodal research for the low-resource Odia language. The dataset was created by manually translating 6,149 English question-answer pairs, each associated with 6,149 unique images from the Visual Genome dataset. This effort resulted in 27,809 English-Odia parallel sentences, ensuring a semantic match with the corresponding visual information. Several baseline experiments were conducted on the dataset, including visual question answering and visual question elicitation. The dataset is the first VQA dataset for the low-resource Odia language and will be released for multimodal research purposes and also help researchers extend for other low-resource languages."
}