Özet:

Today, it is almost impossible to talk about a field that is not affected by developing technology. The field of translation studies has also been significantly affected by technological developments. It is possible to evaluate this impact positively or negatively from different perspectives. On the one hand, the convenience factor offered by current machine translation systems can be considered as an attractive factor; on the other hand, it can be inferred that these developments may pose a serious threat to the translation profession. When we examine the current state of machine translation software in general, there are studies showing that artificial intelligence supported neural systems can provide good results that cannot be underestimated. This study aims to provide a comparative analysis of the technical features and current performance of DeepL Translate and Google Translate translation systems using artificial intelligence-supported neural networks. The comparison has been made on the basis of the same translation tasks between English-Turkish and Turkish-English given to both systems. In order to obtain reliable results, different text types have been used in the translation tasks. The resulting translations have been evaluated by taking the opinion of three different experts with reference to a standard rubric. In the light of the findings obtained from the comparative translation performance of these two machine translation programmes, evaluations have been made on the possible future role of machine translation in the related field and industry.

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