Department of Psychology.
J Exp Psychol Gen. 2020 Jul;149(7):1215-1230. doi: 10.1037/xge0000715. Epub 2019 Dec 2.
It has been suggested that the origins of number words can be traced back to an evolutionarily ancient approximate number system, which represents quantities on a compressed scale and complies with Weber's law. Here, we use a data-driven computational model, which learns to predict 1 event (a word in a text corpus) from associated events, to characterize verbal behavior relative to number words in natural language, without appeal to perception. We show that the way humans use number words in spontaneous language reliably depends on numerical ratio-a clear signature of Weber's law-thus, perfectly mirroring the human and nonhuman psychophysical performance in comparative judgments of numbers. Most notably, the adherence to Weber's law is robustly replicated in a wide range of different languages. Together, these findings suggest that the everyday use of number words in language rests upon a preverbal approximate number system, which would affect the handling of numerical information not only at the input level but also at the level of verbal production. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
有人认为，数字词的起源可以追溯到一个古老的近似数量系统，该系统以压缩的规模表示数量，并符合韦伯定律。在这里，我们使用一种数据驱动的计算模型，该模型学习从相关事件中预测 1 个事件（文本语料库中的一个词），以描述相对于自然语言中数字词的言语行为，而无需诉诸感知。我们表明，人类在自发语言中使用数字词的方式可靠地取决于数值比——这是韦伯定律的明显特征——因此，与人类和非人类在比较数字判断中的心理物理表现完全一致。值得注意的是，韦伯定律的一致性在广泛的不同语言中得到了稳健的复制。总之，这些发现表明，语言中日常使用的数字词依赖于一个前语言的近似数量系统，该系统不仅会影响输入级别的数字信息处理，还会影响言语生成级别的数字信息处理。
