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

The dialect of api is one of the Lampung dialects. Students, from elementary school to high school, learn the Lampung language as an effort to preserve the local language. For immigrant students who learn Lampung dialect of api, they should use the Lampung language dictionary to help understand the...

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Bibliographic Details
Published in2021 International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE) pp. 7 - 11
Main Authors Abidin, Zaenal, Permata, Borman, Rohmat Indra, Ardiyatno, Utoro, Rossi, Farli, Jusman, Yessi
Format Conference Proceeding
LanguageEnglish
Published IEEE 27.10.2021
Subjects
Computational modeling
Computer science
Computers
Dictionaries
Electrical engineering
Information technology
lampung sentence translator machine
post-editing
stemming
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Summary:The dialect of api is one of the Lampung dialects. Students, from elementary school to high school, learn the Lampung language as an effort to preserve the local language. For immigrant students who learn Lampung dialect of api, they should use the Lampung language dictionary to help understand the Lampung language. Using the dictionary manually and repeatedly is ineffective and tedious. This study aims to build an initial model of computer-based Lampung language sentence translator machine. The main purpose of the Lampung language sentence translator machine is to help students learn to understand Lampung language sentences with the help of computers automatically. The Lampung language sentence translator machine works by utilizing the Lampung language dictionary. This study made two contributions or novelty. First, dictionary-based Lampung sentence translator machine and dictionary-based Lampung sentence translator machine with additional stemming and post-editing techniques. The Lampung sentence translator machine was tested using 50 Lampung sentences. Translation results were measured by the bilingual evaluation understudy (BLEU) algorithm. In the dictionary-based Lampung sentence translator machine, the translation accuracy is 46.50%, while the dictionary-based Lampung sentence translation machine with additional stemming and post-editing techniques obtains an accuracy of 58.06%.
DOI:10.1109/ICOMITEE53461.2021.9650324