This is the system published in SMT tool contest for ICON-2014 keep all codes into the same directory.

javac SentenceClustering.java

java SentenceClustering train.source train.target

e.g. java SentenceClustering de-en/europarl-v7.de-en.en de-en/europarl-v7.de-en.de

• the o/p file will be saved as

de-en/europarl-v7.de-en.en.cln

de-en/europarl-v7.de-en.de.cln

javac templatePhraseExtraction.java

java templatePhraseExtraction

java templatePhraseExtraction de-en/europarl-v7.de-en.en.cln de-en/europarl-v7.de-en.de.cln 5

• the o/p file will be saved as *.ebmt

If you use any code cite this paper:

@InProceedings {Pal:2014, author = {Pal, Santanu and Srivastava, Ankit and Dandapat, Sandipan and van Genabith, Josef and Liu, Qun and Way, Andy}, title = {{USAAR-DCU Hybrid Machine Translation System for ICON 2014}}, booktitle = {Proceedings of the 11th International Conference on Natural Language Processing}, year = {2014}, address = {Goa, India} }

@InProceedings{pal-naskar-vangenabith:2015:WMT, author = {Pal, Santanu and Naskar, Sudip and van Genabith, Josef}, title = {UdS-Sant: English--German Hybrid Machine Translation System}, booktitle = {Proceedings of the Tenth Workshop on Statistical Machine Translation}, month = {September}, year = {2015}, address = {Lisbon, Portugal}, publisher = {Association for Computational Linguistics}, pages = {152--157}, url = {http://aclweb.org/anthology/W15-3017} }