Duñabeitia, JA., Baciero, A., Antoniou, K., Antoniou, M., Ataman, E., Baus, C., Ben-Shachar, M., Can Çağlar, O., Chromý, J., Comesaña, M., Filip, M., Filipović Đurđević, D., Gillon Dowens, M., Hatzidaki, A., Januška, J., Jusoh, Z., Kanj, R., Young Kim, S., Kırkıcı, B., Leminen, A., Lohndal, T., Yap, NT., Renvall, H., Rothman, R., Royle, P., Santesteban, M., Sevilla, Y., Slioussar, N., Vaughan-Evans, A., Wodniecka, Z., Wulff, S., & Pliatsikas, C. (2022): The Multilingual Picture Database.
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Abstract
The growing interdisciplinary research field of psycholinguistics is in constant need of new and up-to-date tools which will allow researchers to answer complex questions, but also expand on languages other than English, which dominates the field. One type of such tools are picture datasets which provide naming norms for everyday objects. However, existing databases tend to be small in terms of the number of items they include, and have also been normed in a limited number of languages, despite the recent boom in multilingualism research. In this paper we present the Multilingual Picture (Multipic) database, containing naming norms and familiarity scores for 500 coloured pictures, in thirty-two languages or language varieties from around the world. The data was validated with standard methods that have been used for existing picture datasets. This is the first dataset to provide naming norms, and translation equivalents, for such a variety of languages; as such, it will be of particular value to psycholinguists and other interested researchers. The dataset has been made freely available.