Derlem Dilbilimi ile Makine Çevirisinin Tarihsel Gelişimi: Çeviribilimsel Bir İnceleme The Historical Development of Corpus Linguistics and Machine Translation: A Translation Studies Perspective
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Abstract
Technological developments have led to profound transformations in the field of translation, as in many other disciplines. Especially since the 1990s, with the widespread accessibility of computers, computer-assisted translation (CAT) tools and machine translation systems have become increasingly prevalent in translation practice. Today, traditional translation has largely evolved into the post-editing and revision of outputs produced by neural machine translation (NMT) engines and large language models (LLMs). A major milestone in this transformation was the introduction of its neural machine translation system by Google in 2016, which significantly accelerated the technological impact on the field. This impact has become even more evident with the rapid proliferation of contemporary artificial intelligence systems. Accordingly, research on customized machine translation engines and large language models has gained increasing importance. The most fundamental component underlying these customized systems is data, particularly parallel corpora, which have become indispensable for training, tailoring, and improving the quality of such systems. While corpora were traditionally developed mainly for linguistic and descriptive studies, they are now increasingly integrated with technological applications and systematically constructed for neural machine translation engines and large language models. In this context, the present study examines the historical development of corpora, the evolution of machine translation throughout history, and English–Turkish corpus studies.
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