Mitigating Translationese in Low-resource Languages: The Storyboard Approach
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arXiv
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| Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Acceso en línea: | |
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| author | Kuwanto, Garry Urua, Eno-Abasi E. Amuok, Priscilla Amondi Muhammad, Shamsuddeen Hassan Aremu, Anuoluwapo Otiende, Verrah Nanyanga, Loice Emma Nyoike, Teresiah W. Akpan, Aniefon D. Udouboh, Nsima Ab Archibong, Idongesit Udeme Moses, Idara Effiong Ige, Ifeoluwatayo A. Ajibade, Benjamin Awokoya, Olumide Benjamin Abdulmumin, Idris Aliyu, Saminu Mohammad Iro, Ruqayya Nasir Ahmad, Ibrahim Said Smith, Deontae Michaels, Praise-EL Adelani, David Ifeoluwa Wijaya, Derry Tanti Andy, Anietie |
| author_facet | Kuwanto, Garry Urua, Eno-Abasi E. Amuok, Priscilla Amondi Muhammad, Shamsuddeen Hassan Aremu, Anuoluwapo Otiende, Verrah Nanyanga, Loice Emma Nyoike, Teresiah W. Akpan, Aniefon D. Udouboh, Nsima Ab Archibong, Idongesit Udeme Moses, Idara Effiong Ige, Ifeoluwatayo A. Ajibade, Benjamin Awokoya, Olumide Benjamin Abdulmumin, Idris Aliyu, Saminu Mohammad Iro, Ruqayya Nasir Ahmad, Ibrahim Said Smith, Deontae Michaels, Praise-EL Adelani, David Ifeoluwa Wijaya, Derry Tanti Andy, Anietie |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_10152 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Mitigating Translationese in Low-resource Languages: The Storyboard Approach Kuwanto, Garry Urua, Eno-Abasi E. Amuok, Priscilla Amondi Muhammad, Shamsuddeen Hassan Aremu, Anuoluwapo Otiende, Verrah Nanyanga, Loice Emma Nyoike, Teresiah W. Akpan, Aniefon D. Udouboh, Nsima Ab Archibong, Idongesit Udeme Moses, Idara Effiong Ige, Ifeoluwatayo A. Ajibade, Benjamin Awokoya, Olumide Benjamin Abdulmumin, Idris Aliyu, Saminu Mohammad Iro, Ruqayya Nasir Ahmad, Ibrahim Said Smith, Deontae Michaels, Praise-EL Adelani, David Ifeoluwa Wijaya, Derry Tanti Andy, Anietie Computation and Language I.2.7 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. |
| title | Mitigating Translationese in Low-resource Languages: The Storyboard Approach |
| topic | Computation and Language I.2.7 |
| url | https://arxiv.org/abs/2407.10152 |