Syllable Complexity and Morphological Synthesis: A Well-Motivated Positive Complexity Correlation Across Subdomains

Frontiers in Psychology

article

Shelece Easterday¹  Matthew Stave²  Marc Allassonnière-Tang²  Frank Seifart³ 

[1] Department of Linguistics, University of Hawai'i Mãnoa, United States;Université Lumière Lyon 2 and Centre National de la Recherche Scientifique;Leibniz-Centre General Linguistics (ZAS)

关键词: complexity correlations;    syllable structure;    morphological synthesis;    grammaticalization;    language change;    linguistic typology;    corpus study;   

DOI  :  10.3389/fpsyg.2021.638659

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

Relationships between phonological and morphological complexity have long been proposed in the linguistic literature, with empirical investigations often seeking complexity trade-offs. Positive complexity correlations tend not to be viewed in terms of motivations. We argue that positive complexity correlations can be diachronically well-motivated, emerging from crosslinguistically prevalent processes of language change. We examine the correlation between syllable complexity and morphological synthesis, hypothesizing that the process of grammaticalization motivates a positive relationship between the two features. To test this, we conduct a typological survey of 95 diverse languages and a corpus study of 21 languages with substantive (predominantly >10,000 words) corpora from the DoReCo project. The first study establishes a significant positive correlation between syllable complexity, measured in terms of maximal syllable patterns, and the index of synthesis (morpheme/word ratio). The second study tests the hypothesis that the relationship between syllable complexity and synthesis holds at local (word-initial and word-final) levels and within noun and verb types, as predicted by a grammaticalization account. While the findings of the corpus study are limited in their statistical power, the observed tendencies are consistent with our predictions. This study contributes important findings to the complexity literature, as well as a novel method which incorporates broad typological sampling and deep corpus analysis.

【 授权许可】

CC BY