A review on Indonesian machine translation

Open

F. Rahutomo, A.A. Septarina, M. Sarosa, A. Setiawan, M.M. Huda

2019 Journal of Physics: Conference Series Vol. 1402 Issue 7 Conference paper Cited by 5 SDG 9SDG 16 Quartile

Abstract

Nowadays, machine translation has important role in general communication. The need for machine translation system is higher in this era, resolving culture and nation boundary. Finding correct and optimal translation is not an easy task in language processing. Several machine translation system already exists, but the quality of the translation needed to be improved further. This paper discusses machine translation researches that involve Indonesian language to the other languages by systematic literature review. This paper exposes different approaches and tools for machine translation. The approaches also use various evaluation methods to measure the performance. Moreover, this paper proposes several future works to improve the machine translation quality of Indonesian to the other languages. The review results show that the attention-based approach is being increasingly used to improve the performance of neural machine translation. The translation performance quality depends on the number of the corpus, well-behaved aligned corpus, and the technique used. © 2019 IOP Publishing Ltd.

Affiliations

Information Technology Department, State Polytechnic of Malang, Jl Soekarno Hatta No. 9, Malang, Indonesia; Electrical Engineering Department, State Polytechnic of Malang, Jl Soekarno Hatta No. 9, Malang, Indonesia

Research at a Glance

Premium content — register to unlock

Research at a Glance

Register to unlock

Topics & SDG Alignment

Premium content — register to unlock

Topics & SDG Alignment

Register to unlock

Collaboration

Premium content — register to unlock

Collaboration

Register to unlock

Author Profile (Selected)

Premium content — register to unlock

Author Profile (Selected)

Register to unlock

References Overview

Premium content — register to unlock

References Overview

Register to unlock

Journal & Source

Premium content — register to unlock

Journal & Source

Register to unlock

Metadata & Integrity

Premium content — register to unlock

Metadata & Integrity

Register to unlock