音韵学
语义学(计算机科学)
一般化
正字法
计算机科学
自然语言处理
一致性(知识库)
人工智能
阅读(过程)
心理学
认知心理学
语言学
数学
数学分析
哲学
程序设计语言
作者
Joanne Taylor,Kim Plunkett,Kate Nation
摘要
Two experiments explored learning, generalization, and the influence of semantics on orthographic processing in an artificial language. In Experiment 1, 16 adults learned to read 36 novel words written in novel characters. Posttraining, participants discriminated trained from untrained items and generalized to novel items, demonstrating extraction of individual character sounds. Frequency and consistency effects in learning and generalization showed that participants were sensitive to the statistics of their learning environment. In Experiment 2, 32 participants were preexposed to the sounds of all items (lexical phonology) and to novel definitions for half of these items (semantics). Preexposure to either lexical phonology or semantics boosted the early stages of orthographic learning relative to Experiment 1. By the end of training, facilitation was restricted to the semantic condition and to items containing low-frequency inconsistent vowels. Preexposure reduced generalization, suggesting that enhanced item-specific learning was achieved at the expense of character-sound abstraction. The authors' novel paradigm provides a new tool to explore orthographic learning. Although the present findings support the idea that semantic knowledge supports word reading processes, they also suggest that item-specific phonological knowledge is important in the early stages of learning to read.
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