Centre for Cognitive Neuroscience, Free University Berlin, Germany.
Centre for Language Studies, Radboud University Nijmegen, Netherlands.
Cognition. 2020 Jan;194:104056. doi: 10.1016/j.cognition.2019.104056. Epub 2019 Nov 14.
When adults learn new languages, their speech often remains noticeably non-native even after years of exposure. These non-native variants ('accents') can have far-reaching socio-economic consequences for learners. Many factors have been found to contribute to a learners' proficiency in the new language. Here we examine a factor that is outside of the control of the learner, linguistic similarities between the learner's native language (L1) and the new language (Ln). We analyze the (open access) speaking proficiencies of about 50,000 Ln learners of Dutch with 62 diverse L1s. We find that a learner's L1 accounts for 9-22% of the variance in Ln speaking proficiency. This corresponds to 28-69% of the variance explained by a model with controls for other factors known to affect language learning, such as education, age of acquisition and length of exposure. We also find that almost 80% of the effect of L1 can be explained by combining measures of phonological, morphological, and lexical similarity between the L1 and the Ln. These results highlight the constraints that a learner's native language imposes on language learning, and inform theories of L1-to-Ln transfer during Ln learning and use. As predicted by some proposals, we also find that L1-Ln phonological similarity is better captured when subcategorical properties (phonological features) are considered in the calculation of phonological similarities.
当成年人学习新语言时,即使经过多年的接触,他们的口语往往仍然明显带有非母语口音。这些非母语变体(“口音”)会对学习者的社会经济产生深远的影响。许多因素被发现有助于学习者在新语言中的熟练程度。在这里,我们研究了一个学习者无法控制的因素,即学习者的母语(L1)和新语言(Ln)之间的语言相似性。我们分析了大约 50000 名具有 62 种不同母语的 Ln 荷兰语学习者的(开放获取)口语能力。我们发现,学习者的 L1 占 Ln 口语熟练程度方差的 9-22%。这相当于控制其他已知影响语言学习的因素(如教育、习得年龄和接触时间)的模型所解释的方差的 28-69%。我们还发现,L1 对 Ln 学习和使用的影响的近 80%可以通过在 L1 和 Ln 之间的语音、形态和词汇相似性的测量中进行组合来解释。这些结果强调了学习者的母语对语言学习的限制,并为 Ln 学习和使用过程中的 L1 到 Ln 迁移理论提供了信息。正如一些提议所预测的那样,我们还发现,当在语音相似性的计算中考虑子范畴特性(语音特征)时,L1-Ln 语音相似性可以更好地捕捉到。