人类和黑猩猩的两种数学定义的表达性语言结构

Robert Langs M.D., Anthony F. Badalamenti Ph.D., Sue Savage-Rumbaugh Ph.D.
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引用次数: 12

摘要

人类和黑猩猩的两种表达性语言结构已经被数学鉴定出来。第一个是通过测量调用新单词或符号之间的等待时间发现的,它始终产生单独的特征速率常数和下降的指数曲线,反映了随机合法的泊松过程。第二个是通过计算单词使用的累积信息复杂性(熵)发现的,在所有情况下,熵都是在交际序列中使用到给定点的单词数量的确定性合法对数函数。个体和物种在遵守这一规律方面的差异也体现了样本的特点。从类人猿身上得到的结果与莎士比亚等人类诗人的作品相似。研究结果表明,类人猿的深层、自然、非习得的表达性语言结构与人类相当。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Two mathematically defined expressive language structures in humans and chimpanzees

Two expressive language structures have been identified mathematically in humans and chimpanzees. The first was found by measuring the waiting times between the invocation of new words or symbols, which consistently yielded individually characteristic rate constants and descending exponential curves that reflect a stochastically lawful Poisson process. The second was discovered by calculating the cumulative informational complexity (entropy) of word usage, which in all cases was a deterministically lawful logarithmic function of the number of words used to a given point in a communicative sequence. Individual and species differences in how this law is obeyed also characterized the sample. The results from the apes resembled those from the works of human poets like Shakespeare. The findings speak for deep, natural, unlearned expressive language structures in apes that are comparable to those seen in humans.

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