Evaluation of domain sulfur industry for DIA translator using bilingual evaluation understudy method

Huda Mohammed Lateef, Ahmad Muter Awaad, Diadeen Ali Hameed, Ghanim Thiab Hasa, Tahseen Ameen Faisal

Abstract


Evaluation is important part of our system development cycle; it also contributes to improving new machine translation (MT) technology optimum via comparing them with the traditional systems available to determine the weaknesses and the effectiveness to be improved in the proposed MT system. This work aiming to make a study that evaluate the performance and effectivness of the domain sulfur industry (DSI) for English-Arabic DIA translator quality. The recent study has conducted evaluating by making a comparison between this programme with the prominent Google translator through applying a rendering of 1,200 English sentences in bilingual evaluation understudy (BLUE) method. The obtain results show that the efficiency of Google translator is about 30.325%, while DIA translator efficiency in domain sulfur industry is about 73.325% and it’s more effective and give a better translation accuracy. The BLUE method efficiency is about (90.478%) compared with the human expert evaluator.

Keywords


Bilingual evaluation understudy method; Evaluation English-Arabic machine translation; Evaluation machine translation; Machine translation; Neural approach machine translation

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DOI: https://doi.org/10.11591/eei.v13i1.4489

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Bulletin of EEI Stats

Bulletin of Electrical Engineering and Informatics (BEEI)
ISSN: 2089-3191, e-ISSN: 2302-9285
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).