TY - JOUR
T1 - The Multilingual Picture Database
AU - Duñabeitia, Jon Andoni
AU - Baciero, Ana
AU - Antoniou, Kyriakos
AU - Antoniou, Mark
AU - Ataman, Esra
AU - Baus, Cristina
AU - Ben-Shachar, Michal
AU - Çağlar, Ozan Can
AU - Chromý, Jan
AU - Comesaña, Montserrat
AU - Filip, Maroš
AU - Đurđević, Dušica Filipović
AU - Dowens, Margaret Gillon
AU - Hatzidaki, Anna
AU - Januška, Jiří
AU - Jusoh, Zuraini
AU - Kanj, Rama
AU - Kim, Say Young
AU - Kırkıcı, Bilal
AU - Leminen, Alina
AU - Lohndal, Terje
AU - Yap, Ngee Thai
AU - Renvall, Hanna
AU - Rothman, Jason
AU - Royle, Phaedra
AU - Santesteban, Mikel
AU - Sevilla, Yamila
AU - Slioussar, Natalia
AU - Vaughan-Evans, Awel
AU - Wodniecka, Zofia
AU - Wulff, Stefanie
AU - Pliatsikas, Christos
N1 - Publisher Copyright:
© 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85134625270&partnerID=8YFLogxK
U2 - 10.1038/s41597-022-01552-7
DO - 10.1038/s41597-022-01552-7
M3 - Article
C2 - 35864133
AN - SCOPUS:85134625270
SN - 2052-4463
VL - 9
JO - Scientific data
JF - Scientific data
IS - 1
M1 - 431
ER -