ABSTRACT

Research suggests that second language words are learned faster when they are similar in phonological structure or accent to the words of an individual’s first language. Many major theories suggest this happens because of differences in frequency of exposure and context between first and second language words. Here, we examine the independent contribution of accent and phonological structure on the speed of word learning and on the depth of semantic encoding while controlling for frequency of exposure and context. Fifteen participants learned novel words associated with abstract shapes in a paired associates task. The words systematically varied in their accent and phonological structure. Learning speed was measured for each word and the depth of semantic encoding was measured via a novel manipulation of the N300 ERP component in a Picture Recognition Task of the learned items. Both non-native structure and accent slowed word learning and differences in the N300 effect indicated that semantic encoding was shallower for words with a non-native than native phonological structure, despite almost ceiling levels of accuracy. These results are consistent with a model of second language learning that proposes both accent and phonological structure influence how fast and deep new language vocabulary is learnt.

摘要

研究表明，当第二语言单词的语音结构或口音与个人第一语言的单词相似时，它们的学习速度会更快。许多主要理论认为，这是因为第一语言和第二语言单词之间的暴露频率和上下文存在差异。在这里，我们检查了口音和语音结构对单词学习速度和语义编码深度的独立贡献，同时控制了暴露频率和上下文。15 名参与者在配对联想任务中学习了与抽象形状相关的新词。这些词在口音和语音结构上系统地变化。测量每个单词的学习速度，并通过在学习项目的图片识别任务中对 N300 ERP 组件的新操作来测量语义编码的深度。非母语结构和口音都减慢了单词学习和 N300 效应的差异，表明语义编码对于具有非母语的单词比母语语音结构更浅，尽管准确度几乎达到上限。这些结果与第二语言学习模型一致，该模型提出口音和语音结构都会影响学习新语言词汇的速度和深度。尽管准确度几乎达到天花板。这些结果与第二语言学习模型一致，该模型提出口音和语音结构都会影响学习新语言词汇的速度和深度。尽管准确度几乎达到天花板。这些结果与第二语言学习模型一致，该模型提出口音和语音结构都会影响学习新语言词汇的速度和深度。