Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

The Application of Computer-Aided Under-Resourced Language Translation for Malay into Kadazandusun

Domaine:

natural language processing

Type de record:

paper
Créateur:
MohMinSurAsn
Éditeur:
Int
Hôte:
A computer-aided language translation using a Machine translation (MT) is an application performed by computers (machines) that translates one natural language to another. There are many online language translation tools, but thus far none offers a sequence of text translations for the under-resourced Kadazandusun language. Although there are web-based and mobile applications of Kadazandusun dictionaries available, the systems do not translate more than one word. Hence, this paper aims to present the discussion of the preliminary translation of Malay to Kadazandusun. The basic word-to-word with dictionary alignment translation based on Direct Machine Translation (DMT) is selected to begin the exploration of the translation domain where DMT is one of the earliest translation methods which relies on the word-to-word approach (sequence-to-sequence model). This paper aims to investigate the under-resourced language and the task of translating from the Malay language to the Kadazandusun language or vice versa. This paper presents the application and the process as well as the results of the system according to the basic Kadazandusun word arrangement (Verb-Subject-Object) and its translation quality using the Bilingual Evaluation Understudy (BLEU) score. Several phases are involved during the process, including data collection (word pair translation), preprocessing, text selection, translation procedures, and performance evaluation. The preliminary language translation approach is proven to be capable of producing up to 0.5 BLEU scores which indicate that the translation is readable, however, requires post-editing for better comprehension. The findings are significant for the quality of the under-resourced language translation and as a starting point for other machine translation methodologies such as statistical or deep learning-based translation.

Visit

doi.org

Tasks

machine translation

Licenses

http://creativecommons.org/licenses/by/4.0

Similaires

Author identification for Under-Resourced language (KadazanDusun)Minimal Dependency Translation: a Framework for Computer-Assisted Translation for Under-Resourced LanguagesApplication of Machine Translation in Localization into Low-Resourced LanguagesComputer-aided Translation Based on Lampung Language as Low Resource LanguageTransforming Computer-Aided Manufacturing – The Revolutionary Application of Artificial IntelligenceDocument Classification for the Under-resourced Amharic Language

Author identification for Under-Resourced language (KadazanDusun)

This paper presents the task of Author Identification for KadazanDusun language by using

Minimal Dependency Translation: a Framework for Computer-Assisted Translation for Under-Resourced Languages

This paper introduces Minimal Dependency Translation (MDT), an ongoing project to develop a rule-bas

Application of Machine Translation in Localization into Low-Resourced Languages

Computer-aided Translation Based on Lampung Language as Low Resource Language

Transforming Computer-Aided Manufacturing – The Revolutionary Application of Artificial Intelligence

Unlike some major regions in the world, the sub-Saharan African manufacturing sector performs poorly

Document Classification for the Under-resourced Amharic Language

NLP is severely hampered by a scarcity of digital resources. This is especially true for Amharic, a