Using corpus statistics to evaluate nonce words

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Abstract

Nonce words are widely used in linguistic research to evaluate areas such as the acquisition of vowel harmony and consonant voicing, naturalness judgment of loanwords, and children's acquisition of morphemes. Researchers usually create lists of nonce words intuitively by considering the phonotactic features of the target languages. In this study, a corpus of Turkish orthographic representations is used to propose a measure for the nonce word appropriateness for linearly concatenative languages. The conditional probabilities of orthographic co-occurrences and pairwise vowel collocations within the same word boundaries are used to evaluate a list of nonce words in terms of whether they would be rejected, moderately accepted or fully accepted as novel words. A group of 50 Turkish native speakers was asked to judge the same list of nonce words on how native-like the words sound. Both the model and the participants displayed similar results. © 2014 Springer-Verlag Berlin Heidelberg.

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Kiliç, Ö. (2014). Using corpus statistics to evaluate nonce words. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8607 LNCS, pp. 26–35). Springer Verlag. https://doi.org/10.1007/978-3-662-44116-9_3

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