Evaluating English to Arabic machine translators

Author

Hailat, Taghreed ; Al-Kabi, Mohammed N. ; Alsmadi, Izzat M. ; Al-Shawakfa, Emad

fYear

2013

fDate

3-5 Dec. 2013

Firstpage

1

Lastpage

6

Abstract

Location and language have now less impact as barriers for the expansion and the spread of information around the world. Machine translators achieve such a tedious task of translation among languages in quick and reliable manners. However, if compared with human translation, issues related to semantic meanings may always arise. Different machine translators may differ in their effectiveness, and they can be evaluated either by humans or through the use of automatic methods. In this study, we attempt to evaluate the effectiveness of two popular Machine Translation (MT) systems (Google Translate and Babylon machine translation systems) to translate sentences from English to Arabic, where an automatic evaluation method called Bilingual Evaluation Understudy (BLEU) is used. Our preliminary tests indicated that Google Translate system is more effective in translating English sentences into Arabic in comparison with the Babylon MT system.

Keywords

language translation; natural language processing; BLEU; Babylon MT system; Babylon machine translation systems; Bilingual Evaluation Understudy; English-to-Arabic machine translator evaluation; Google Translate MT system; automatic evaluation method; semantic meanings; sentence translation; Computational linguistics; Computers; Conferences; Electrical engineering; Google; Internet; Measurement; Arabic MT; Automatic Evaluation of Machine Translation; BLEU; English MT; statistical MT;

fLanguage

English

Publisher

ieee

Conference_Titel

Applied Electrical Engineering and Computing Technologies (AEECT), 2013 IEEE Jordan Conference on

Conference_Location

Amman

Print_ISBN

978-1-4799-2305-2

Type

conf

DOI

10.1109/AEECT.2013.6716439

Filename

6716439