仍无证据表明非母语者比例对自然语言复杂性有影响。

IF 2.1 3区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY
Entropy Pub Date : 2024-11-18 DOI:10.3390/e26110993
Alexander Koplenig
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引用次数: 0

摘要

在最近的一项研究中,我证明了大量的 L2(第二语言)使用者似乎并不会影响自然语言的形态学或信息论复杂性。本文有三个主要目的:首先,我回应了最近对我的分析提出的批评,表明批评者提出的观点在我最初的研究中已经得到了明确的考虑和分析。此外,我还表明,所提出的替代分析经不起详细推敲。其次,我引入了关于自然语言信息论复杂性的新数据,这些数据来自各种语言模型--从简单的统计模型到先进的神经网络--基于一个包含 40 个多语言文本集的数据库,这些文本集代表了广泛的文本类型。第三,我使用新方法重新分析了信息理论和形态复杂性数据,这些方法更好地考虑了参数估计中模型的不确定性,以及语言的谱系相关性和地理邻近性。结果与我之前的研究结果一致,没有证据表明大量的 L2 说话者会对自然语言的复杂性产生影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Still No Evidence for an Effect of the Proportion of Non-Native Speakers on Natural Language Complexity.

In a recent study, I demonstrated that large numbers of L2 (second language) speakers do not appear to influence the morphological or information-theoretic complexity of natural languages. This paper has three primary aims: First, I address recent criticisms of my analyses, showing that the points raised by my critics were already explicitly considered and analysed in my original work. Furthermore, I show that the proposed alternative analyses fail to withstand detailed examination. Second, I introduce new data on the information-theoretic complexity of natural languages, with the estimates derived from various language models-ranging from simple statistical models to advanced neural networks-based on a database of 40 multilingual text collections that represent a wide range of text types. Third, I re-analyse the information-theoretic and morphological complexity data using novel methods that better account for model uncertainty in parameter estimation, as well as the genealogical relatedness and geographic proximity of languages. In line with my earlier findings, the results show no evidence that large numbers of L2 speakers have an effect on natural language complexity.

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来源期刊
Entropy
Entropy PHYSICS, MULTIDISCIPLINARY-
CiteScore
4.90
自引率
11.10%
发文量
1580
审稿时长
21.05 days
期刊介绍: Entropy (ISSN 1099-4300), an international and interdisciplinary journal of entropy and information studies, publishes reviews, regular research papers and short notes. Our aim is to encourage scientists to publish as much as possible their theoretical and experimental details. There is no restriction on the length of the papers. If there are computation and the experiment, the details must be provided so that the results can be reproduced.
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