Evidence of Visual Statistical Learning in the Reading of Unspaced Chinese Sentences

Jenn Yeu Chen, Tsanyu Wang

研究成果: 會議貢獻類型會議論文同行評審

摘要

Chinese texts are renowned for the lack of physical spaces between words in a sentence. Reading these sentences requires a stage of word segmentation, the mechanism of which may involve visual statistical learning. In three experiments employing the RSVP task along with the Saffran et al. (1997) paradigm, we provided evidence that foreign learners of Chinese could capture the statistical information embedded in a string of characters and use that information to tell apart a “word” from a “nonword”. The statistical learning effect (.57) was comparable to that observed previously in an auditory task using the same stimuli. The results of the experiments also suggested that significant visual statistical learning required a conscious level of processing that directed the participants’ attention at the characters as well as an unconscious level, at which the distributional information across the characters can be continuously computed and accumulated.

原文英語
頁面2665-2670
頁數6
出版狀態已發佈 - 2021
事件43rd Annual Meeting of the Cognitive Science Society: Comparative Cognition: Animal Minds, CogSci 2021 - Virtual, Online, 奥地利
持續時間: 2021 7月 262021 7月 29

會議

會議43rd Annual Meeting of the Cognitive Science Society: Comparative Cognition: Animal Minds, CogSci 2021
國家/地區奥地利
城市Virtual, Online
期間2021/07/262021/07/29

ASJC Scopus subject areas

  • 認知神經科學
  • 人工智慧
  • 電腦科學應用
  • 人機介面

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