Abstract
Research on Translation Style in Machine Learning Based on Linguistic Quantitative Characteristics Perception
Highlights
It is possible to make a contrastive analysis of target texts or translations by using the structural features of language measurement
Metrological linguistics holds that the differences in language styles of translations are caused by the differences in the frequency of language units used.[3,4] In our opinion, since translation is a kind of re-creation and a kind of literary work, different linguistic styles and linguistic features will appear in different translations
The different linguistic quantitative characteristics (LQC) formed by authors in language expression can be quantitatively used as a statistical feature to analyze language style.[8]. In other words, language style is due to differences in the frequency of use of language units
Summary
It is possible to make a contrastive analysis of target texts or translations by using the structural features of language measurement. Such studies have not yet been reported. Machine translation, including online translation, and human translation are bound to produce different language styles and linguistic features in terms of language expression and syntactic structure. These differences are known as “stylistic differences” and are caused by. As with the linguistic style of literary works, these differences can be expressed by some statistical features of metrological linguistics. By combining our results with the statistical data obtained from the corpus method, we qualitatively discuss the form characteristics of different languages
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