Evaluating the Effectiveness of Machine Translation in Preserving Metaphorical Expressions from Source Texts to Target Languages

Matyakubova, Laylo

Lingvospektr · 2024-yil

Annotatsiya

With the rapid proliferation of Neural Machine Translation (NMT) systems, questions persist about their ability to handle nuanced linguistic phenomena—particularly metaphorical expressions. Metaphors are culturally and contextually embedded, and their translation involves more than a direct lexical substitution. This article investigates the effectiveness of state-of-the-art machine translation (MT) systems in preserving metaphorical expressions from source languages to target languages. We first review the theoretical foundations of metaphor in cognitive linguistics and the challenges they present to MT. We then examine the evolution of MT models, from statistical to neural approaches, assessing their capacity for handling figurative language. Drawing on empirical studies and a newly constructed bilingual parallel corpus enriched with carefully annotated metaphorical expressions, we perform a qualitative and quantitative evaluation of leading NMT systems. Our findings suggest that while neural models have improved in fluency and contextual coherence, they often fail to fully preserve the conceptual structure and pragmatic force of metaphors. We identify the linguistic factors influencing metaphor translation quality—such as cultural specificity, metaphorical density, and syntactic complexity—and consider methods to improve metaphor handling, including pre-training strategies, metaphor-aware datasets, and post-editing tools. By elucidating the current limitations and potential improvements, we advance the understanding of how MT systems grapple with one of the most creative and conceptually rich aspects of human language.

Maqola ma’lumotlari
MualliflarMatyakubova, Laylo
JurnalLingvospektr
NashriyotЎзбекистон давлат жаҳон тиллари университети, “Modern Scientific Research” MChJ
ISSN3060-4958
Nashr sanasi2024-12-17
Jild3
Son1
Betlar247-254
TilIngliz
Ilmiy sohaFilologiya
Indeksga qo‘shilgan2026-08-29

Maqolaning asl sahifasi

Kalit so‘zlar

машинный перевод, метафора, нейронный машинный перевод, образный язык, межъязыковая семантика, mashina tarjimasi, metafora, neyron mashina tarjimasi, badiiy til, tillararo semantika, Machine translation, Metaphor, Neural machine translation, Figurative language, Cross-linguistic semantics

Ilmiy soha

Filologiya

Iqtibos keltirish

APAMatyakubova, Laylo (2024). Evaluating the Effectiveness of Machine Translation in Preserving Metaphorical Expressions from Source Texts to Target Languages. Lingvospektr, 3(1), 247-254. https://lingvospektr.uz/index.php/lngsp/article/view/192
GOST (OAK)Matyakubova, Laylo Evaluating the Effectiveness of Machine Translation in Preserving Metaphorical Expressions from Source Texts to Target Languages // Lingvospektr. – 2024. – T. 3, № 1. – P. 247-254.
MLAMatyakubova, Laylo. “Evaluating the Effectiveness of Machine Translation in Preserving Metaphorical Expressions from Source Texts to Target Languages.” Lingvospektr, 3(1), 247-254, 2024. https://lingvospektr.uz/index.php/lngsp/article/view/192
ChicagoMatyakubova, Laylo. “Evaluating the Effectiveness of Machine Translation in Preserving Metaphorical Expressions from Source Texts to Target Languages.” Lingvospektr, 3(1), 247-254 (2024). https://lingvospektr.uz/index.php/lngsp/article/view/192
HarvardMatyakubova, Laylo (2024) ‘Evaluating the Effectiveness of Machine Translation in Preserving Metaphorical Expressions from Source Texts to Target Languages’, Lingvospektr, 3(1), 247-254. https://lingvospektr.uz/index.php/lngsp/article/view/192
BibTeX
@article{matyakubovalaylo2024,
  title = {Evaluating the Effectiveness of Machine Translation in Preserving Metaphorical Expressions from Source Texts to Target Languages},
  author = {Matyakubova, Laylo},
  journal = {Lingvospektr},
  year = {2024},
  volume = {3},
  number = {1},
  pages = {247-254},
  url = {https://lingvospektr.uz/index.php/lngsp/article/view/192}
}

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