Does simplification hold true for machine translations? A corpus-based analysis of lexical diversity in text varieties across genres

Abstract

Extensive studies have described the linguistic features of human translations and verified the existence of the simplification translation universal. However, little has been known about the linguistic features of machine translations, although machine translation, as a unique modality of translation, has become an integral part of translation practice. This study is intended to test whether the simplification translation universal observed in human translations also holds true for machine translations. If so, are simplification features in machine translations different significantly from those in human translations? And does genre significantly affect simplification features? To this end, we built a balanced comparable corpus containing three text varieties, i.e., machine translations, human translations and target-language originals across three genres namely contemporary novels, government documents and academic abstracts. Based on the corpus, we conducted a systematic comparison of lexical diversity, as a proxy for simplification, of different text varieties. The results show that simplification is corroborated overall in both machine and human translations when compared with target-language originals, and machine translations are more simplified than human translations. Additionally, genre is found to exert a significant influence on the lexical diversity of different text varieties. This study is expected to expand the scope of corpus-based translation studies on the one hand and to offer insights into the improvement of machine translation systems on the other hand.