Open AccessMachine Translation Quality in Mobile Apps for Text-based Image Translation
Author(s) -
Eglė Miltakienė
Publication year - 2021
Publication title -
vertimo studijos
Language(s) - English
Resource type - Journals
eISSN - 2424-3590
pISSN - 2029-7033
DOI - 10.15388/vertstud.2021.4
Subject(s) - lithuanian , machine translation , computer science , translation (biology) , quality (philosophy) , natural language processing , artificial intelligence , example based machine translation , evaluation of machine translation , machine translation software usability , information retrieval , linguistics , philosophy , biochemistry , chemistry , epistemology , messenger rna , gene
With the advancement of mobile applications, now it is possible to perform instant text translation using a smartphone’s camera. Because text translation within images is still a relatively new field of research, it is not surprising that the translation quality of these mobile applications is under-researched. This study aims to determine the image-to-text translation quality in the English to Lithuanian language direction using popular machine translation apps. To classify errors and evaluate the quality of translation, the present study adopts and customizes the Multidimensional Quality Metrics (MQM) framework (Lommel 2014). The obtained results indicate that image-to-text machine translation apps produce exceptionally low-quality translations for the English-Lithuanian language pair. Therefore, the quality of machine translation for low-resource languages such as Lithuanian remains an issue.