A neural machine translation system for Kreol Repiblik Moris and English

Although Google Translate is a widely used machine translation service that supports 133 languages, it does not incorporate support for the Kreol Repiblik Moris (KRM) language. Addressing this limitation, the current research focuses on enhancing the accuracy and fluency of machine translation between KRM and English through natural language processing and deep neural machine translation techniques. In this study, a machine translation system using a transformer model trained with a dataset of 50,000 parallel corpora has been developed. The model was evaluated using manual translations and the bilingual evaluation understudy (BLEU) score. A score of 31.46 for translating from KRM to English and 28.15 for translating from English to KRM was achieved. To our knowledge, these are the highest BLEU scores for translation between these two languages. This is due to utilising the largest dataset and extensive atomic words from the KRM dictionary. This successful interdisciplinary funded project led to the setting up of a free online translation service and a smartphone app for Mauritian citizens and tourists.

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Publication Details

Journal
IAES International Journal of Artificial Intelligence
Published
2024-10-08
DOI
https://doi.org/10.11591/ijai.v13.i4.pp4976-4987
Citations
2
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
0.69
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article

A neural machine translation system for Kreol Repiblik Moris and English

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2 citations
IAES International Journal of Artificial Intelligence
Natural Language Processing Techniques
0.69
article

A neural machine translation system for Kreol Repiblik Moris and English

Vandanah Gooria, Sheeba Armoogum, Nirmal Kumar Betchoo, Aneerav Sukhoo, Sameerchand Pudaruth, Abdallah Peerally, Mohammad Zafar Khodabocus
article en
2 citations

Abstract

Although Google Translate is a widely used machine translation service that supports 133 languages, it does not incorporate support for the Kreol Repiblik Moris (KRM) language. Addressing this limitation, the current research focuses on enhancing the accuracy and fluency of machine translation between KRM and English through natural language processing and deep neural machine translation techniques. In this study, a machine translation system using a transformer model trained with a dataset of 50,000 parallel corpora has been developed. The model was evaluated using manual translations and the bilingual evaluation understudy (BLEU) score. A score of 31.46 for translating from KRM to English and 28.15 for translating from English to KRM was achieved. To our knowledge, these are the highest BLEU scores for translation between these two languages. This is due to utilising the largest dataset and extensive atomic words from the KRM dictionary. This successful interdisciplinary funded project led to the setting up of a free online translation service and a smartphone app for Mauritian citizens and tourists.

IAES International Journal of Artificial IntelligenceVol. 13(4)
Open University of Mauritius (MU), MemorialCare Health System (US), University of Mauritius (MU)
Quality Education
Openalex Percentile: Top 24%
Natural Language Processing Techniques
0.69
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