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. 2022 Dec;51(6):1247-1265.
doi: 10.1007/s10936-022-09884-6. Epub 2022 Aug 5.

Constructing Pseudowords with Constraints on Morphological Features - Application for Polish Pseudonouns and Pseudoverbs

Joanna Daria Dołżycka  1   2   3 , Jan Nikadon  4   5 , Magdalena Formanowicz  4   5
Affiliations

Constructing Pseudowords with Constraints on Morphological Features - Application for Polish Pseudonouns and Pseudoverbs

Joanna Daria Dołżycka et al. J Psycholinguist Res. 2022 Dec.

Abstract

Pseudowords allow researchers to investigate multiple grammatical or syntactic aspects of language processing. In order to serve that purpose, pseudoword stimuli need to preserve certain properties of real language. We provide a Python-based pipeline for the generation of pseudoword stimuli that sound/read naturally in a given language. The pseudowords are designed to resemble real words and clearly indicate their grammatical class for languages that use specific suffixes from parts of speech. We also provide two sets of pseudonouns and pseudoverbs in Polish that are outcomes of the applied pipeline. The sets are equipped with psycholinguistically relevant properties of words, such as orthographic Levenshtein distance 20. We also performed two studies (overall N = 640) to test the validity of the algorithmically constructed stimuli in a human sample. Thus, we present stimuli that were deprived of direct meaning yet are clearly classifiable as grammatical categories while being orthographically and phonologically plausible.

Keywords: Grammar; Linguistic processing; Pseudowords; Psycholinguistics; Wuggy.

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Conflict of interest statement

The authors declare no conflict of interest. This research was funded by the National Science Centre, Poland (OPUS 14: 2017/27/B/HS6/01049), and has been approved by the Ethical Committee of Psychology Department of Nicolaus Copernicus University in Toruń (decision no. 9/2018). Prior to taking part in the studies presented in this article, participants provided informed consent.

The authors declare no conflict of interest.

Figures

Fig. 1
Fig. 1
Schematic depiction of pseudoword generation pipelines used in Study 1 and 2. Further implementation details are provided in the main text and Python code is provided in the SOM
See this image and copyright information in PMC

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