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 |
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| Title of host publication | ICSIE 2018 - Proceedings of the 7th International Conference on Software and Information Engineering |
| Publisher | Association for Computing Machinery (ACM) |
| Pages | 131-135 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781450364690 |
| DOIs | |
| 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