  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.
