| Revista: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560733 |
| ISSN: | 1405-5546 |
| Autors: | Khenglawt, Vanlalmuansangi1 Laskar, Sahinur Rahman2 Pakray, Partha2 Manna, Riyanka3 Khan, Ajoy Kumar1 |
| Institucions: | 1Mizoram University, Department of Computer Engineering, India 2National Institute of Technology, Department of Computer Science and Engineering, Texas. Estados Unidos 3Gandhi Institute Of Technology And Management, Department of Computer Science and Engineering, Andhra Pradesh. India |
| Any: | 2022 |
| Període: | Jul-Sep |
| Volum: | 26 |
| Número: | 3 |
| Paginació: | 1377-1398 |
| País: | México |
| Idioma: | Inglés |
| Resumen en inglés | Machine translation is one of the most powerful natural language processing applications for preserving and upgrading low-resource language. Mizo language is considered as low-resource since there is limited availability of resources. Therefore, it is a challenging task for English-Mizo language pair translation. Moreover, Mizo is a tonal language, where a word can express different meanings depending on a variety of tones. There are four variations of tones, namely high, low, rising, and falling. A tone marker is used to represent each of the tones, which is added to the vowels to indicate tone variation. Addressing tonal words in machine translation for such a low-resource pair is another challenging issue. In this paper, the English-Mizo corpus is developed where parallel sentences having tonal words are incorporated. The different machine translation models are explored based on statistical machine translation and neural machine translation for the baseline systems. Furthermore, the proposed approach attempts to augment the train data by expanding parallel data having tonal words and achieves state-of-the-art results for both forward and backward translations encountering tonal words. |
| Keyword: | English-Mizo, Machine translation, Low-resource, Tonal |
| Text complet: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
