Francesca Di Giovanni
Minimal parsimonious chunking of written language: investigating the storage-computation trade-off as a driving principle in chunk formation.
Rel. Alessandro Pelizzola, Davide Crepaldi. Politecnico di Torino, Corso di laurea magistrale in Physics Of Complex Systems (Fisica Dei Sistemi Complessi), 2021
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Abstract
Visual word identification is the process that allows the brain to recognize a familiar and meaningful word from an ordered collection of letters. Chunking seems to play an important role in this process: rather than jumping from single letters to words, the brain seems to group letters in smaller units. Some recent studies suggest to oust morphemes, the smallest meaning-bearing units in language, from their role as building blocks in chunking: they should instead be replaced by letter chunks which do not necessarily have an explicit connection with semantics, but which could be explained by statistical regularities in letter co-occurence. However, the exact principles according to which these chunks emerge in skilled readers are still unclear.
The algorithm developed in the thesis tries to answer this question, looking for the set of chunks that optimizes the trade-off between the storage of many different units and the computational effort needed to process completely new words
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