ABSTRACT

Dependency distance (DD) is a well-established measure of syntactic complexity. Previous studies largely focused on the linear dimension, mostly by mean of dependency distance (MDD). In the present study, a new quantitative indicator –mean hierarchical dependency distance (MHDD), is proposed to discuss DD-related issues. Combining MHDD and MDD, the study investigates syntactic complexity of different texts, using strictly length-controlled sentences of 12 text types from the Freiburg-Brown corpus of American English. Correlations of MHDD and MDD have been identified, and possible reasons are discussed from the mathematical and theoretical perspectives. Mathematically, one is that the numerator of MHDD overlaps with the denominator of MDD, both being (n-1) where n is the number of words in the sentence. The other is that the denominator of MHDD (maximum hierarchical layer: MAXHL) and the numerator of MDD (sum of DD: SOD), are positively correlated. We believe that it is the positive correlation of SOD and MAXHL that ensures the change of MDD and MHDD in the same direction. It is also worth noting that both MAXHL and SOD seem to be minimized at their respective data spectrum, which foreshadows the dependency distance minimization (DDM) tendency on the hierarchical dimension.

摘要

依赖距离 (DD) 是句法复杂度的一种成熟的度量。以前的研究主要集中在线性维度上，主要是通过依赖距离 (MDD)。在本研究中，提出了一个新的定量指标——平均层次依赖距离（MHDD）来讨论与 DD 相关的问题。结合 MHDD 和 MDD，该研究使用来自美国英语 Freiburg-Brown 语料库的 12 种文本类型的严格长度控制的句子来调查不同文本的句法复杂性。已经确定了MHDD和MDD的相关性，并从数学和理论的角度讨论了可能的原因。在数学上，一个是 MHDD 的分子与 MDD 的分母重叠，两者都是 (n-1)，其中 n 是句子中的单词数。另一个是MHDD的分母（最大层次层：MAXHL）和MDD的分子（DD之和：SOD）是正相关的。我们认为，正是 SOD 和 MAXHL 的正相关保证了 MDD 和 MHDD 同向变化。还值得注意的是，MAXHL 和 SOD 似乎都在各自的数据频谱上被最小化，这预示了分层维度上的依赖距离最小化 (DDM) 趋势。