Koplenig Alexander
Department of Lexical Studies, Leibniz Institute for the German Language (IDS), 68161 Mannheim, Germany.
Entropy (Basel). 2024 Nov 18;26(11):993. doi: 10.3390/e26110993.
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.
在最近的一项研究中,我证明了大量的第二语言使用者似乎不会影响自然语言的形态或信息论复杂性。本文有三个主要目标:第一,我回应最近对我分析的批评,表明批评者提出的观点在我原来的工作中已经被明确考虑和分析过。此外,我表明所提出的替代分析经不起详细审查。第二,我引入了关于自然语言信息论复杂性的新数据,这些估计来自各种语言模型——从简单的统计模型到基于40个多语言文本集合数据库的先进神经网络,这些文本集合代表了广泛的文本类型。第三,我使用新方法重新分析信息论和形态复杂性数据,这些方法能更好地考虑参数估计中的模型不确定性,以及语言的谱系相关性和地理邻近性。与我早期的研究结果一致,结果表明没有证据表明大量的第二语言使用者会对自然语言复杂性产生影响。