Premium
An Extension of a Parallel‐Distributed Processing Framework of Reading Aloud in Japanese: Human Nonword Reading Accuracy Does Not Require a Sequential Mechanism
Author(s) -
Ikeda Kenji,
Ueno Taiji,
Ito Yuichi,
Kitagami Shinji,
Kawaguchi Jun
Publication year - 2017
Publication title -
cognitive science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.498
H-Index - 114
eISSN - 1551-6709
pISSN - 0364-0213
DOI - 10.1111/cogs.12382
Subject(s) - reading (process) , computer science , grapheme , mechanism (biology) , reading aloud , natural language processing , speech recognition , artificial intelligence , orthography , parsing , linguistics , philosophy , physics , graphene , epistemology , quantum mechanics
Humans can pronounce a nonword (e.g., rint). Some researchers have interpreted this behavior as requiring a sequential mechanism by which a grapheme‐phoneme correspondence rule is applied to each grapheme in turn. However, several parallel‐distributed processing ( PDP ) models in English have simulated human nonword reading accuracy without a sequential mechanism. Interestingly, the Japanese psycholinguistic literature went partly in the same direction, but it has since concluded that a sequential parsing mechanism is required to reproduce human nonword reading accuracy. In this study, by manipulating the list composition (i.e., pure word/nonword list vs. mixed list), we demonstrated that past psycholinguistic studies in Japanese have overestimated human nonword reading accuracy. When the more fairly reevaluated human performance was targeted, a newly implemented Japanese PDP model simulated the target accuracy as well as the error patterns. These findings suggest that PDP models are a more parsimonious way of explaining reading across various languages.