Mitigating Translationese in Low-resource Languages: The Storyboard Approach
Abstract
Low-resource languages often face challenges in acquiring high-quality language data due to the reliance on translation-based methods, which can introduce the translationese effect. This phenomenon results in translated sentences that lack fluency and naturalness in the target language. In this paper, we propose a novel approach for data collection by leveraging storyboards to elicit more fluent and natural sentences. Our method involves presenting native speakers with visual stimuli in the form of storyboards and collecting their descriptions without direct exposure to the source text. We conducted a comprehensive evaluation comparing our storyboard-based approach with traditional text translation-based methods in terms of accuracy and fluency. Human annotators and quantitative metrics were used to assess translation quality. The results indicate a preference for text translation in terms of accuracy, while our method demonstrates worse accuracy but better fluency in the language focused.
Cite
@article{arxiv.2407.10152,
title = {Mitigating Translationese in Low-resource Languages: The Storyboard Approach},
author = {Garry Kuwanto and Eno-Abasi E. Urua and Priscilla Amondi Amuok and Shamsuddeen Hassan Muhammad and Anuoluwapo Aremu and Verrah Otiende and Loice Emma Nanyanga and Teresiah W. Nyoike and Aniefon D. Akpan and Nsima Ab Udouboh and Idongesit Udeme Archibong and Idara Effiong Moses and Ifeoluwatayo A. Ige and Benjamin Ajibade and Olumide Benjamin Awokoya and Idris Abdulmumin and Saminu Mohammad Aliyu and Ruqayya Nasir Iro and Ibrahim Said Ahmad and Deontae Smith and Praise-EL Michaels and David Ifeoluwa Adelani and Derry Tanti Wijaya and Anietie Andy},
journal= {arXiv preprint arXiv:2407.10152},
year = {2024}
}
Comments
published at LREC-COLING 2024