通过语言和非语言变量预测欧洲密切相关语言的可理解性有多好?

Charlotte Gooskens, V. V. Heuven
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引用次数: 18

摘要

我们测量了欧洲16种密切相关的口语的相互理解程度。使用相同的统一方法(完形填空测试)确定所有70种语言组合的可理解性。我们分析了1833名听众的结果,他们代表了来自16个国家的受过教育的年轻欧洲人之间的相互理解程度。词汇、音系、正字法、形态和句法距离作为语言变量计算。我们还量化了非语言变量(例如,暴露,对测试语言的态度)。采用逐步回归分析,评估了70对语言对相互可理解性的语言和非语言预测因子的重要性。接触测试语言是最重要的变量,凌驾于所有其他变量之上。然后,将分析限制在固有可理解性的预测上,我们分析了之前没有或很少接触测试语言的听众子集的结果。语言上的距离,尤其是词汇上的距离,现在可以解释很大一部分的差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How well can intelligibility of closely related languages in Europe be predicted by linguistic and non-linguistic variables?
We measured mutual intelligibility of 16 closely related spoken languages in Europe. Intelligibility was determined for all 70 language combinations using the same uniform methodology (a cloze test). We analysed the results of 1833 listeners representing the mutual intelligibility between young, educated Europeans from the same 16 countries. Lexical, phonological, orthographic, morphological and syntactic distances were computed as linguistic variables. We also quantified non-linguistic variables (e.g. exposure, attitudes towards the test languages). Using stepwise regression analysis the importance of linguistic and non-linguistic predictors for the mutual intelligibility in the 70 language pairs was assessed. Exposure to the test language was the most important variable, overriding all other variables. Then, limiting the analysis to the prediction of inherent intelligibility, we analysed the results for a subset of listeners with no or little previous exposure to the test language. Linguistic distances, especially lexical distance, now explain a substantial part of the variance.
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