The Multilingual Picture Database

Jon Andoni Duñabeitia, Ana Baciero, Kyriakos Antoniou, Mark Antoniou, Esra Ataman, Cristina Baus, Michal Ben-Shachar, Ozan Can Çağlar, Jan Chromý, Montserrat Comesaña, Maroš Filip, Dušica Filipović Đurđević, Margaret Gillon Dowens, Anna Hatzidaki, Jiří Januška, Zuraini Jusoh, Rama Kanj, Say Young Kim, Bilal Kırkıcı, Alina LeminenTerje Lohndal, Ngee Thai Yap, Hanna Renvall, Jason Rothman, Phaedra Royle, Mikel Santesteban, Yamila Sevilla, Natalia Slioussar, Awel Vaughan-Evans, Zofia Wodniecka, Stefanie Wulff, Christos Pliatsikas

Research output: Journal PublicationArticlepeer-review

7 Citations (Scopus)

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.

Original languageEnglish
Article number431
JournalScientific data
Volume9
Issue number1
DOIs
Publication statusPublished - Dec 2022

ASJC Scopus subject areas

  • Statistics and Probability
  • Information Systems
  • Education
  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Library and Information Sciences

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