Syntactic complexity in translated and non-translated texts: A corpus-based study of simplification

PLoS One. 2021 Jun 24;16(6):e0253454. doi: 10.1371/journal.pone.0253454. eCollection 2021.

Abstract

This study approaches the investigation of the simplification hypotheses in corpus-based translation studies from a syntactic complexity perspective. The research is based on two comparable corpora, the English monolingual part of COCE (Corpus of Chinese-English) and the native English corpus of FLOB (Freiburg-LOB Corpus of British English). Using the 13 syntactic complexity measures falling into five subconstructs (i.e. length of production unit, amount of subordination, amount of coordination, phrasal complexity and overall sentence complexity), our results show that translation as a whole is less complex compared to non-translation, reflected most prominently in the amount of subordination and overall sentence complexity. Further pairwise comparison of the four subgenres of the corpora shows mixed results. Specifically, the translated news is homogenous to native news as evidenced by the complexity measures; the translated genres of general prose and academic writing are less complex compared to their native counterparts while translated fiction is more complex than non-translated fiction. It was found that mean sentence length always produced a significant effect on syntactic complexity, with higher syntactic complexity for longer sentence lengths in both corpora. ANOVA test shows a highly significant main effect of translation status, with higher syntactic complexity in the non-translated texts (FLOB) than the translated texts (COCE), which provides support for the simplification hypothesis in translation. It is also found that, apart from translation status, genre is an important variable in affecting the complexity level of translated texts. Our study offers new insights into the investigation of simplification hypothesis from the perspective of translation from English into Chinese.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Humans
  • Semantics*
  • Translating*

Grants and funding

This research was funded by a General Research Fund (GRF) grant (Ref: 15605520) from the Research Grants Council of Hong Kong. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.