We present a computational analysis of three language varieties: native, advanced non-native, and translation. Our goal is to investigate the similarities and differences between non-native language productions and translations, contrasting both with native language. Using a collection of computational methods we establish three main results: (1) the three types of texts are easily distinguishable; (2) non-native language and translations are closer to each other than each of them is to native language; and (3) some of these characteristics depend on the source or native language, while others do not, reflecting, perhaps, unified principles that similarly affect translations and non-native language.
Corpus-based investigation of translationese has been a prolific field of recent research, laying out an empirical foundation for the theoretically motivated hypotheses on the characteristics of translationese. More specifically, identification of translated texts by means of automatic classification shed light on the manifestation of translation universals and cross-linguistic influences as markers of translated texts , while @cite_1 introduced a dataset for investigation of potential common traits between translations and non-native texts. Such studies prove to be important for the development of parallel corpora , the improvement in quality of plagiarism detection , language modeling, and statistical machine translation .
@cite_1
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Providing an examination of translation as an interpretative process which encompasses its wide-ranging nature, this work presents a descriptive frame and tries to capture the creative potential of the translation process. It outlines the six essential elements and the five stages of translation, recognizes the three main types of translation, and discusses the personal, creative and cultural influences which can affect a translated piece, as well as the possible applications of computer analysis.