Automatic Detection of Omission in Comparative Literary Translation

Abstract

Omission is considered a controversial issue in translation research. On the one hand, it is regarded as one of the common translation techniques used in cases of non-equivalence or implicit conveyance of meaning. On the other hand, it may be viewed as a sign of failure of the translator to render the Original Texts (OT) properly into the Target Languages (TL). Moreover, in some cases it may be considered as a parameter of manipulation and censorship. For this reason, when carrying out comparative translation research, the detection of omission and its analysis is one of the key elements to evaluate a translation, and to gain a full understanding of the translation decisions taken by a translator. In most cases, the process of detecting cases of omission in comparative research is carried out by manually annotating the Target Text (TT) in comparison to the OT, an arduous and time-consuming task, above all in long and extensive texts, such as some literary texts. For this reason, in this casestudy, we use an alternative semi-automatic method to detect omission in translation research, and we use corpus analysis to provide results. Finally, we propose the creation of a new and more appropriate tool for the precise and automatic detection of omission, aimed at helping to obtain more results and a wider perspective in comparative literary translation studies.