UniPseudo: A universal pseudoword generator.

Pseudoword generator lexical decision

Journal

Quarterly journal of experimental psychology (2006)
ISSN: 1747-0226
Titre abrégé: Q J Exp Psychol (Hove)
Pays: England
ID NLM: 101259775

Informations de publication

Date de publication:
18 Apr 2023
Historique:
pubmed: 10 3 2023
medline: 10 3 2023
entrez: 9 3 2023
Statut: aheadofprint

Résumé

Pseudowords are letter strings that look like words but are not words. They are used in psycholinguistic research, particularly in tasks such as lexical decision. In this context, it is essential that the pseudowords respect the orthographic statistics of the target language. Pseudowords that violate them would be too easy to reject in a lexical decision and would not enforce word recognition on real words. We propose a new pseudoword generator, UniPseudo, using an algorithm based on Markov chains of orthographic n-grams. It generates pseudowords from a customizable database, which allows one to control the characteristics of the items. It can produce pseudowords in any language, in orthographic or phonological form. It is possible to generate pseudowords with specific characteristics, such as frequency of letters, bigrams, trigrams, or quadrigrams, number of syllables, frequency of biphones, and number of morphemes. Thus, from a list of words composed of verbs, nouns, adjectives, or adverbs, UniPseudo can create pseudowords resembling verbs, nouns, adjectives, or adverbs in any language using an alphabetic or syllabic system.

Identifiants

pubmed: 36891822
doi: 10.1177/17470218231164373
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

17470218231164373

Auteurs

Boris New (B)

Laboratoire Psychologie et Neurocognition, CNRS UMR 5105, University Savoie Mont Blanc (USMB), Chambéry, France.

Jessica Bourgin (J)

Laboratoire Psychologie et Neurocognition, CNRS UMR 5105, University Savoie Mont Blanc (USMB), Chambéry, France.

Julien Barra (J)

Laboratoire Psychologie et Neurocognition, CNRS UMR 5105, University Savoie Mont Blanc (USMB), Chambéry, France.

Christophe Pallier (C)

Cognitive Neuroimaging Unit, INSERM, CEA, CNRS, Université Paris-Saclay, NeuroSpin Center, Gif/Yvette, France.

Classifications MeSH