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Sentence frequency norms for psycholinguistic studies

Stéphane Dufau
Marjorie Armando
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Jonathan Grainger


Capitalizing on the Google’s Ngram corpus, we examined the possibility to establish frequency norms for sentences in a format suitable for psycholinguistics. Ngram corpus is based on over 8 million digitized books and reflects how often sequences of (N-)words are used in a particular language (8 languages available to date). Even though publicly available, raw data is presented in a form that is difficult to use as is. Frequency is split by year and corpus split into multiple files. In addition, sequences tagged with part-of-speech are mixed with non-tagged ones. Here, we propose a simplified and curated version of the Ngram frequency norms that will help in stimulus selection for psycholinguistic studies. Such curated norms are used in a pilot study to assess whether or not sentence frequency plays a role in sentence recognition.
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hal-03808739 , version 1 (10-10-2022)


  • HAL Id : hal-03808739 , version 1


Stéphane Dufau, Marjorie Armando, Jonathan Grainger. Sentence frequency norms for psycholinguistic studies. 61st Annual Meeting of the Psychonomic Society, Nov 2020, Virtual, United States. ⟨hal-03808739⟩
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