RT Journal Article
T1 Human versus Neural Machine Translation Creativity: A Study on Manipulated MWEs in Literature.
A1 Corpas-Pastor, Gloria
A1 Noriega-Santiáñez, Laura
K1 Literatura - Traducción automática
AB In the digital era, the (r)evolution of neural machine translation (NMT) has reshaped both the market and translators’ workflow. However, the adoption of this technology has not fully reached the creative field of literary translation. Against this background, this study aims to explore to what extent NMT systems can be used to translate the creative challenges posed by idioms, specifically manipulated multiword expressions (MWEs) found in literary texts. To carry out this pilot study, five manipulated MWEs were selected from a fantasy novel and machine-translated (English > Spanish) by four NMT systems (DeepL, Google Translate, Bing Translator, and Reverso). Then, each NMT output as well as a human translation are assessed by six professional literary translators by using a human evaluation sheet. Based on these results, the creativity obtained in each translation method was calculated. Despite the satisfactory performance of both DeepL and Google Translate, HT creativity was highly superior in almost all manipulated MWEs. To the best of our knowledge, this paper not only contributes to the ongoing study of NMT applied to literature, but it is also one of the few studies that delve into the almost unexplored field of assessing creativity in neural machine-translated MWEs.
PB MDPI
YR 2024
FD 2024-09-02
LK https://hdl.handle.net/10630/34784
UL https://hdl.handle.net/10630/34784
LA eng
NO Corpas Pastor, G.; Noriega-Santiáñez, L. Human versus Neural Machine Translation Creativity: A Study on Manipulated MWEs in Literature. Information 2024, 15, 530. https://doi.org/10.3390/info15090530
NO This research is funded by a predoctoral contract granted by the University of Malaga and it has been carried out in the framework of several research projects: “Multi-lingual and Multi-domain Adaptation for the Optimisation of the VIP system” (VIP II, ref. no. PID2020-112818GB-I00/AEI/10.13039/501100011033, 2021–2025, Spanish Ministry of Science and Innovation), and “Multilingual machine interpretation for COVID-19 cases in emergency departments” (RECOVER, ref. ProyExcel_00540, 2022–2025, Andalusian Regional Government). Partial funding for open access charge: Universidad de Málaga
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026