Recurrent Neural Network-Gated Recurrent Unit for Indonesia-Sentani Papua Machine Translation
The Papuan Sentani language is spoken in the city of Jayapura, Papua. The law states the need to preserve regional languages. One of them is by building an Indonesian-Sentani Papua translation machine. The problem is how to build a translation machine and what model to choose in doing so. The model...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Informatics Department, Faculty of Computer Science Bina Darma University
2023-12-01
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| Series: | Journal of Information Systems and Informatics |
| Subjects: | |
| Online Access: | https://journal-isi.org/index.php/isi/article/view/597 |
| _version_ | 1797351885213007872 |
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| author | Rizkial Achmad Yokelin Tokoro Jusuf Haurissa Andik Wijanarko |
| author_facet | Rizkial Achmad Yokelin Tokoro Jusuf Haurissa Andik Wijanarko |
| author_sort | Rizkial Achmad |
| collection | DOAJ |
| description | The Papuan Sentani language is spoken in the city of Jayapura, Papua. The law states the need to preserve regional languages. One of them is by building an Indonesian-Sentani Papua translation machine. The problem is how to build a translation machine and what model to choose in doing so. The model chosen is Recurrent Neural Network – Gated Recurrent Units (RNN-GRU) which has been widely used to build regional languages in Indonesia. The method used is an experiment starting from creating a parallel corpus, followed by corpus training using the RNN-GRU model, and the final step is conducting an evaluation using Bilingual Evaluation Understudy (BLEU) to find out the score. The parallel corpus used contains 281 sentences, each sentence has an average length of 8 words. The training time required is 3 hours without using a GPU. The result of this research was that a fairly good BLEU score was obtained, namely 35.3, which means that the RNN-GRU model and parallel corpus produced sufficient translation quality and could still be improved. |
| first_indexed | 2024-03-08T13:07:09Z |
| format | Article |
| id | doaj.art-47c96d426d3d4205afeccaec21e797f8 |
| institution | Directory Open Access Journal |
| issn | 2656-5935 2656-4882 |
| language | English |
| last_indexed | 2024-03-08T13:07:09Z |
| publishDate | 2023-12-01 |
| publisher | Informatics Department, Faculty of Computer Science Bina Darma University |
| record_format | Article |
| series | Journal of Information Systems and Informatics |
| spelling | doaj.art-47c96d426d3d4205afeccaec21e797f82024-01-18T15:58:29ZengInformatics Department, Faculty of Computer Science Bina Darma UniversityJournal of Information Systems and Informatics2656-59352656-48822023-12-01541449146010.51519/journalisi.v5i4.597597Recurrent Neural Network-Gated Recurrent Unit for Indonesia-Sentani Papua Machine TranslationRizkial Achmad0Yokelin Tokoro1Jusuf Haurissa2Andik Wijanarko3Universitas Sains dan TeknologiUniversitas CenderawasihUniversitas Sains dan TeknologiUniversitas Amikom PurwokertoThe Papuan Sentani language is spoken in the city of Jayapura, Papua. The law states the need to preserve regional languages. One of them is by building an Indonesian-Sentani Papua translation machine. The problem is how to build a translation machine and what model to choose in doing so. The model chosen is Recurrent Neural Network – Gated Recurrent Units (RNN-GRU) which has been widely used to build regional languages in Indonesia. The method used is an experiment starting from creating a parallel corpus, followed by corpus training using the RNN-GRU model, and the final step is conducting an evaluation using Bilingual Evaluation Understudy (BLEU) to find out the score. The parallel corpus used contains 281 sentences, each sentence has an average length of 8 words. The training time required is 3 hours without using a GPU. The result of this research was that a fairly good BLEU score was obtained, namely 35.3, which means that the RNN-GRU model and parallel corpus produced sufficient translation quality and could still be improved.https://journal-isi.org/index.php/isi/article/view/597machine translation, rnn-gru, papua, indonesia |
| spellingShingle | Rizkial Achmad Yokelin Tokoro Jusuf Haurissa Andik Wijanarko Recurrent Neural Network-Gated Recurrent Unit for Indonesia-Sentani Papua Machine Translation Journal of Information Systems and Informatics machine translation, rnn-gru, papua, indonesia |
| title | Recurrent Neural Network-Gated Recurrent Unit for Indonesia-Sentani Papua Machine Translation |
| title_full | Recurrent Neural Network-Gated Recurrent Unit for Indonesia-Sentani Papua Machine Translation |
| title_fullStr | Recurrent Neural Network-Gated Recurrent Unit for Indonesia-Sentani Papua Machine Translation |
| title_full_unstemmed | Recurrent Neural Network-Gated Recurrent Unit for Indonesia-Sentani Papua Machine Translation |
| title_short | Recurrent Neural Network-Gated Recurrent Unit for Indonesia-Sentani Papua Machine Translation |
| title_sort | recurrent neural network gated recurrent unit for indonesia sentani papua machine translation |
| topic | machine translation, rnn-gru, papua, indonesia |
| url | https://journal-isi.org/index.php/isi/article/view/597 |
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