NEURAL MACHINE TRANSLATION OF PHRASAL VERBS IN LITERARY PARALLEL CORPORA: A CONTEXTUAL AND SEMANTIC ANALYSIS OF TRANSFORMER-BASED MODELS
https://doi.org/10.5281/zenodo.19873874
Kalit so‘zlar
Neural Machine Translation (NMT), phrasal verbs, literary translation, parallel corpora, transformer models, attention mechanisms, idiomatic expressions, multiword expressions (MWEs), contextual semantics, corpus-based analysis.Annotasiya
This study reveals at the problems and improvements in translating phrasal verbs in literary texts using Neural Machine Translation (NMT). Today, because the world is more connected, there is a higher need for translations that are both correct and sensitive to context. Modern NMT systems, especially those based on transformer models, work better than older rule-based and statistical methods. One important advantage of these systems is that they can understand meaning from context by using attention mechanisms. This makes them useful for translating difficult expressions like phrasal verbs. For this reason, it is important to have a clear and simple method to study and evaluate how these translations are done.
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