DocumentCode :
3693919
Title :
Phoneme-based English-Amharic Statistical Machine Translation
Author :
Mulu Gebreegziabher Teshome;Laurent Besacier;Girma Taye;Dereje Teferi
Author_Institution :
IT Doctoral Program, Addis Ababa University, Addis Ababa, Ethiopia
fYear :
2015
Firstpage :
1
Lastpage :
5
Abstract :
This research considers the application of Statistical method to automatic Machine Translation (MT) from English to Amharic. The research focuses on improving the translation quality by applying phonemic transcription on the target side, which is Amharic. Accordingly, the BLEU score results for the phoneme-based EASMT system is 37.53% a gain of 2.21 BLEU point from another baseline phrase-based EASMT with a BLEU score result of 35.32%. This clearly shows that phoneme-based translation outperforms the baseline system.
Keywords :
"Vocabulary","Training","Electronic mail","Computers","Morphology","Tuning","Medical services"
Publisher :
ieee
Conference_Titel :
AFRICON, 2015
Electronic_ISBN :
2153-0033
Type :
conf
DOI :
10.1109/AFRCON.2015.7331921
Filename :
7331921
Link To Document :
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