It is often stated that human languages, as other biological systems, are shaped by cost-cutting pressures but, to what extent? Attempts to quantify the degree of optimality of languages by means of an optimality score have been scarce and focused mostly on English. Here we recast the problem of the optimality of the word order of a sentence as an optimization problem on a spatial network where the vertices are words, arcs indicate syntactic dependencies and the space is defined by the linear order of the words in the sentence. We introduce a new score to quantify the cognitive pressure to reduce the distance between linked words in a sentence. The analysis of sentences from 93 languages representing 19 linguistic families reveals that half of languages are optimized to a 70% or more. The score indicates that distances are not significantly reduced in a few languages and confirms two theoretical predictions, i.e. that longer sentences are more optimized and that distances are more likely to be longer than expected by chance in short sentences. We present a new hierarchical ranking of languages by their degree of optimization. The statistical advantages of the new score call for a reevaluation of the evolution of dependency distance over time in languages as well as the relationship between dependency distance and linguistic competence. Finally, the principles behind the design of the score can be extended to develop more powerful normalizations of topological distances or physical distances in more dimensions.
翻译:通常有人说,人类语言与其他生物系统一样,受成本削减压力的影响,但程度如何?试图以最佳程度评分的方式量化语言的最佳程度,但这种尝试是稀缺的,而且主要侧重于英语。在这里,我们重新将一个句子的字顺序优化问题作为空间网络的一个优化问题,在空间网络中,句子是单词,弧法表明综合依赖性,用句子的线性顺序界定空间。我们采用新的评分,量化认知压力,以减少一个句子中相联词的距离。对代表19个语言家庭93种语言的量刑分析显示,半数语言的优化程度为70%或70%以上。评分表明,少数语言的距离没有大大缩短,并证实了两种理论预测,即句子更优化,短句子的距离比预期要长得多。我们以其优化程度对语言进行新的等级排序。新评分的统计优势要求重新评价依赖性距离的变异程度,在语言设计上更远的距离上,可以在语言的高度上发展。