Bottom-up probabilistic information in visual word recognition: interactions with phonological and morphological functions. (March 2020)

• Record Type: Journal Article
• Authors: Celata, Chiara
• Is Part Of: Language sciences. Volume 78(2020)
• Publication Date: 2020-03
• Subjects: Phonotactic probabilities -- Lexical access -- Masked fragment priming -- Consonant clusters -- Prefixation -- Italian; Linguistics -- Periodicals; Language and languages -- Periodicals; Linguistique -- Périodiques; Langage et langues -- Périodiques; Language and languages; Linguistics; Periodicals; Electronic journals; 405
• DOI: 10.1016/j.langsci.2019.101267
• Languages: English
• ISSNs: 0388-0001

Abstract

Abstract: This study investigates the role of probabilistic phonotactics in the processing of consonant clusters (as opposed to consonant-vowel sequences) and of complex words (as opposed to monomorphemic words) in two experiments of visual word recognition with masked fragment priming. Target words are more efficiently recognized when the transition probabilities between an initial fragment and the following segment in the target are high, but this effect is not equally distributed across all areas of the phonology. It was found that speakers rely more heavily on transition probabilities between segments of a consonant cluster than between segments of a consonant-vowel sequence. The morphemic integrity of the cluster is also a relevant parameter in predicting the role of probabilistic phonotactics in lexical access, with prefixed items showing a stronger facilitatory effect than pseudoprefixed items. Taken together, these findings demonstrate that phonotactic probabilities are relevant in visual word recognition, and that their effects interact with higher order linguistic information. These findings also enrich our view of the selection-and-competition mechanism that governs written word processing by providing direct evidence of the fact that the speakers anticipate the segment to the right based on implicit knowledge of phonotactic probabilities. Highlights: Native speakers of Italian are sensitive to probabilistic phonotactics in visual word recognition. Speakers' reliance on transition probabilities changes with changing phonological and morphological conditions. Reliance on transition probabilities changes with changing sizes of the sequence over which probabilities are calculated. General processing mechanisms based on the statistics of the lexicon are shaped by higher-order linguistic functions.