A computational model of word recognition (Baayen, Milin, Djurdjevic, The trial-level accuracy was best predicted by a model that included the corpus frequencies of Accuracy on this task was reliably above chance, and N-grams were then paired up and used in a relative frequency decision task (e.g. Subjective frequency ratings collected for 352 n-grams showed a strong correlation withĬorpus frequency, in particular for n-grams with the highest subjective frequency. Investigated the capacity of people to gauge the absolute and relative frequencies of n-grams. Words has also been extensively studied and linked to performance on linguistic tasks. To the frequency effects in word reading and lexical decision. N-grams that occurred less frequently (Arnon & Snider, 2010), an effect that is analogous N-grams that occurred more frequently in a large corpus of English were read faster than What properties of the n-gram influence the respondent? It has been recently shown that When asked to think about the subjective frequency of an n-gram (a group of n words),
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