RT Conference Proceedings
T1 How can Paidiom improve the neural machine translation of idioms?
A1 Hidalgo Ternero, Carlos Manuel
K1 Traducción automática
K1 Modismos - Traducción automática
K1 Traducción -  Innovaciones tecnológicas
AB In this paper we present research results with Paidiom, a text-preprocessing algorithm designed for 1) converting discontinuous multiword expressions (MWEs) into their continuous forms and 2) translemmatising them, i.e., converting source-text MWEs into their target-text equivalents, in order to improve the performance of current neural machine translation (NMT) systems. To test its effectiveness, an experiment with the NMT systems of VIP, Google Translate and DeepL has been carried out in the ES>EN translation direction with Verb-Noun Idiomatic Constructions (VNICs) in Spanish. The performance of Paidiom was compared to both the one of our previous algorithm (gApp) and to the manual conversion (our gold standard). In this regard, the promising results yielded by this study, the first one analysing Paidiom’s performance, will shed some light on new avenues for enhancing MWE-aware NMT systems.
YR 2023
FD 2023
LK https://hdl.handle.net/10630/28196
UL https://hdl.handle.net/10630/28196
LA eng
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 25 ene 2026