Example-based english to Arabic machine translation: Matching stage using internal medicine publications

Rana Ehab; Eslam Amer; Mahmoud Gadallah

doi:10.1145/3220267.3220294

Example-based english to Arabic machine translation: Matching stage using internal medicine publications

Rana Ehab
, Eslam Amer
, Mahmoud Gadallah

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Automatic machine translation becomes an important source of translation nowadays. It is a software system that translates a text from one natural language to one (many) natural language. On the web, there are many machine translation systems that give the reasonable translation, although the systems are not very good. Medical records contain complex information that must be translated correctly according to its medical meaning not its English meaning only. So, the quality of a machine translation in this domain is very important. In this paper, we present using matching stage from Example-Based Machine Translation technique to translate a medical text from English as source language to Arabic as the target language. We have used 259 medical sentences that are extracted from internal medicine publications for our system. Experimental results on BLUE metrics showed a decreased performance 0.486 comparing to GOOGLE translation which has an accuracy result about 0.536.

Original language	English
Title of host publication	ICSIE 2018 - Proceedings of the 7th International Conference on Software and Information Engineering
Publisher	Association for Computing Machinery
Pages	131-135
Number of pages	5
ISBN (Electronic)	9781450364690
DOIs	https://doi.org/10.1145/3220267.3220294
Publication status	Published - 2 May 2018
Event	7th International Conference on Software and Information Engineering, ICSIE 2018 - Cairo, Egypt Duration: 2 May 2018 → 4 May 2018

Conference

Conference	7th International Conference on Software and Information Engineering, ICSIE 2018
Country/Territory	Egypt
City	Cairo
Period	2/05/18 → 4/05/18

Keywords

Automatic machine translation
Example-Based Machine
Natural Language Processing

Access to Document

10.1145/3220267.3220294

Cite this

@inproceedings{637a94586ffa4889bb39c7b5dd51a717,

title = "Example-based english to Arabic machine translation: Matching stage using internal medicine publications",

abstract = "Automatic machine translation becomes an important source of translation nowadays. It is a software system that translates a text from one natural language to one (many) natural language. On the web, there are many machine translation systems that give the reasonable translation, although the systems are not very good. Medical records contain complex information that must be translated correctly according to its medical meaning not its English meaning only. So, the quality of a machine translation in this domain is very important. In this paper, we present using matching stage from Example-Based Machine Translation technique to translate a medical text from English as source language to Arabic as the target language. We have used 259 medical sentences that are extracted from internal medicine publications for our system. Experimental results on BLUE metrics showed a decreased performance 0.486 comparing to GOOGLE translation which has an accuracy result about 0.536.",

keywords = "Automatic machine translation, Example-Based Machine, Natural Language Processing",

author = "Rana Ehab and Eslam Amer and Mahmoud Gadallah",

note = "Publisher Copyright: {\textcopyright} 2018 Association for Computing Machinery. Noissn.; 7th International Conference on Software and Information Engineering, ICSIE 2018 ; Conference date: 02-05-2018 Through 04-05-2018",

year = "2018",

month = may,

day = "2",

doi = "10.1145/3220267.3220294",

language = "English",

pages = "131--135",

booktitle = "ICSIE 2018 - Proceedings of the 7th International Conference on Software and Information Engineering",

publisher = "Association for Computing Machinery",

address = "United States",

}

Ehab, R, Amer, E & Gadallah, M 2018, Example-based english to Arabic machine translation: Matching stage using internal medicine publications. in ICSIE 2018 - Proceedings of the 7th International Conference on Software and Information Engineering. Association for Computing Machinery, pp. 131-135, 7th International Conference on Software and Information Engineering, ICSIE 2018, Cairo, Egypt, 2/05/18. https://doi.org/10.1145/3220267.3220294

Example-based english to Arabic machine translation: Matching stage using internal medicine publications. / Ehab, Rana; Amer, Eslam; Gadallah, Mahmoud.
ICSIE 2018 - Proceedings of the 7th International Conference on Software and Information Engineering. Association for Computing Machinery, 2018. p. 131-135.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Example-based english to Arabic machine translation

T2 - 7th International Conference on Software and Information Engineering, ICSIE 2018

AU - Ehab, Rana

AU - Amer, Eslam

AU - Gadallah, Mahmoud

PY - 2018/5/2

Y1 - 2018/5/2

N2 - Automatic machine translation becomes an important source of translation nowadays. It is a software system that translates a text from one natural language to one (many) natural language. On the web, there are many machine translation systems that give the reasonable translation, although the systems are not very good. Medical records contain complex information that must be translated correctly according to its medical meaning not its English meaning only. So, the quality of a machine translation in this domain is very important. In this paper, we present using matching stage from Example-Based Machine Translation technique to translate a medical text from English as source language to Arabic as the target language. We have used 259 medical sentences that are extracted from internal medicine publications for our system. Experimental results on BLUE metrics showed a decreased performance 0.486 comparing to GOOGLE translation which has an accuracy result about 0.536.

AB - Automatic machine translation becomes an important source of translation nowadays. It is a software system that translates a text from one natural language to one (many) natural language. On the web, there are many machine translation systems that give the reasonable translation, although the systems are not very good. Medical records contain complex information that must be translated correctly according to its medical meaning not its English meaning only. So, the quality of a machine translation in this domain is very important. In this paper, we present using matching stage from Example-Based Machine Translation technique to translate a medical text from English as source language to Arabic as the target language. We have used 259 medical sentences that are extracted from internal medicine publications for our system. Experimental results on BLUE metrics showed a decreased performance 0.486 comparing to GOOGLE translation which has an accuracy result about 0.536.

KW - Automatic machine translation

KW - Example-Based Machine

KW - Natural Language Processing

UR - https://www.scopus.com/pages/publications/85055472258

U2 - 10.1145/3220267.3220294

DO - 10.1145/3220267.3220294

M3 - Conference contribution

AN - SCOPUS:85055472258

SP - 131

EP - 135

BT - ICSIE 2018 - Proceedings of the 7th International Conference on Software and Information Engineering

PB - Association for Computing Machinery

Y2 - 2 May 2018 through 4 May 2018

ER -

Example-based english to Arabic machine translation: Matching stage using internal medicine publications

Abstract

Conference

Keywords

Access to Document

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Cite this