Bridging the “gApp”: improving neural machine translation systems for multiword expression detection

Author:

Hidalgo-Ternero Carlos Manuel1,Pastor Gloria Corpas1

Affiliation:

1. University of Málaga, Department of Translation and Interpreting, Campus de Teatinos s/n , 29071 - Malaga , Spain

Abstract

Abstract The present research introduces the tool gApp, a Python-based text preprocessing system for the automatic identification and conversion of discontinuous multiword expressions (MWEs) into their continuous form in order to enhance neural machine translation (NMT). To this end, an experiment with semi-fixed verb–noun idiomatic combinations (VNICs) will be carried out in order to evaluate to what extent gApp can optimise the performance of the two main free open-source NMT systems —Google Translate and DeepL— under the challenge of MWE discontinuity in the Spanish into English directionality. In the light of our promising results, the study concludes with suggestions on how to further optimise MWE-aware NMT systems.

Publisher

Walter de Gruyter GmbH

Subject

Linguistics and Language,Communication,Language and Linguistics

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Robust Design of Machine Translation System Based on Convolutional Neural Network;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2024

2. Intelligent English Automatic Translation System Based on Human-Computer Interaction Enhancement Algorithm;2023 Asia-Europe Conference on Electronics, Data Processing and Informatics (ACEDPI);2023-04

3. Optimization of English Machine Translation by Deep Neural Network under Artificial Intelligence;Computational Intelligence and Neuroscience;2022-04-21

4. Reassessing gApp: Does MWE Discontinuity Always Pose a Challenge to Neural Machine Translation?;Computational and Corpus-Based Phraseology;2022

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