TY - GEN
T1 - Developing Indonesian-English hybrid machine translation system
AU - Yulianti, Evi
AU - Budi, Indra
AU - Hidayanto, Achmad Nizar
AU - Manurung, Hisar Maruli
AU - Adriani, Mirna
PY - 2011
Y1 - 2011
N2 - Rule Based Machine Translation (RBMT) and Statistical Machine translation (SMT) have different approach in performing translation task. RBMT uses linguistic rule between two languages which is built manually by human in general, whereas SMT uses co-occurrence statistic of word in parallel corpora. We combine those different approaches into Indonesian-English Hybrid Machine Translation (HMT) system to get the advantage from both kind of information. Initially, Indonesian text is inputted into RBMT. Then, the output will be edited by SMT to generate the final translation of English text. SMT is capable to do this because on the training process, it uses RBMT's output (English) as source material and real translation (English) as target material. Unavailability of ready to use Indonesian-English RBMT system becomes a challenge to do this research. Our study shows that SMT still outperforms HMT by 8.01% in average.
AB - Rule Based Machine Translation (RBMT) and Statistical Machine translation (SMT) have different approach in performing translation task. RBMT uses linguistic rule between two languages which is built manually by human in general, whereas SMT uses co-occurrence statistic of word in parallel corpora. We combine those different approaches into Indonesian-English Hybrid Machine Translation (HMT) system to get the advantage from both kind of information. Initially, Indonesian text is inputted into RBMT. Then, the output will be edited by SMT to generate the final translation of English text. SMT is capable to do this because on the training process, it uses RBMT's output (English) as source material and real translation (English) as target material. Unavailability of ready to use Indonesian-English RBMT system becomes a challenge to do this research. Our study shows that SMT still outperforms HMT by 8.01% in average.
UR - http://www.scopus.com/inward/record.url?scp=84857351674&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84857351674
SN - 9789791421119
T3 - ICACSIS 2011 - 2011 International Conference on Advanced Computer Science and Information Systems, Proceedings
SP - 265
EP - 270
BT - ICACSIS 2011 - 2011 International Conference on Advanced Computer Science and Information Systems, Proceedings
T2 - 2011 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2011
Y2 - 17 December 2011 through 18 December 2011
ER -