对书面语言的大量定量分析挑战了所有语言都同样复杂的想法
Alexander Koplenig1, Sascha Wolfer2, Peter Meyer2
1Department of Lexical Studies, Leibniz Institute for the German Language (IDS), Mannheim, Germany. koplenig@ids-mannheim.de.
Scientific reports
|September 16, 2023
概括
这项研究挑战了所有语言都同样复杂的观念. 利用信息理论和分析成千上万种语言的数十亿个单词,研究人员发现复杂性各不相同,并且与说话人口规模有关.
科学领域:
- 计算语言学 计算语言学
- 信息理论 信息理论
- 语言类型学语言类型学
背景情况:
- 同复杂性假设认为所有人类语言都具有相似的复杂性水平.
- 研究语言复杂性对于理解语言多样性和演变至关重要.
研究的目的:
- 量化评估和比较大量书面语言的复杂性.
- 探索语言复杂性,跨体一致性和说话人口规模之间的关系.
主要方法:
- 在一个庞大的多语言语料库 (3.5亿个单词,9亿个字符,2069种语言) 上训练语言模型.
- 使用统计作为关键指标推断平均预测复杂性.
- 进行了跨语言和跨体的比较分析.
主要成果:
- 语言复杂性,用度来衡量,在所有语言中并不均.
- 复杂度排名在不同公司之间是一致的.
- 语音人口大小显著预测一种语言的.
结论:
- 从信息理论的角度来看,研究结果提供了反对等复杂性假设的证据.
- 语言的复杂性是可量化的,并受到诸如语音人口统计学等因素的影响.
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