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音素的随机模型揭示了其使用的作者依赖性。

Stochastic Model for Phonemes Uncovers an Author-Dependency of Their Usage.

作者信息

Deng Weibing, Allahverdyan Armen E

机构信息

Complexity Science Center & Institute of Particle Physics, Central China Normal University, Wuhan 430079, China.

Yerevan Physics Institute, Alikhanian Brothers Street 2, Yerevan 375036, Armenia.

出版信息

PLoS One. 2016 Apr 8;11(4):e0152561. doi: 10.1371/journal.pone.0152561. eCollection 2016.

Abstract

We study rank-frequency relations for phonemes, the minimal units that still relate to linguistic meaning. We show that these relations can be described by the Dirichlet distribution, a direct analogue of the ideal-gas model in statistical mechanics. This description allows us to demonstrate that the rank-frequency relations for phonemes of a text do depend on its author. The author-dependency effect is not caused by the author's vocabulary (common words used in different texts), and is confirmed by several alternative means. This suggests that it can be directly related to phonemes. These features contrast to rank-frequency relations for words, which are both author and text independent and are governed by the Zipf's law.

摘要

我们研究音素的秩频关系,音素是仍与语言意义相关的最小单位。我们表明,这些关系可以用狄利克雷分布来描述,它是统计力学中理想气体模型的直接类似物。这种描述使我们能够证明文本音素的秩频关系确实取决于其作者。作者依赖性效应不是由作者的词汇(不同文本中使用的常用词)引起的,并且通过几种替代方法得到了证实。这表明它可以直接与音素相关。这些特征与词的秩频关系形成对比,词的秩频关系既与作者无关也与文本无关,并且由齐普夫定律支配。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/25a3/4825982/02bd428451f3/pone.0152561.g001.jpg

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