@inproceedings{byrne-etal-2003-johns,
title = "The {J}ohns {H}opkins {U}niversity 2003 {C}hinese-{E}nglish machine translation system",
author = "Byrne, W. and
Khudanpur, S. and
Kim, W. and
Kumar, S. and
Pecina, P. and
Virga, P. and
Xu, P. and
Yarowsky, D.",
booktitle = "Proceedings of Machine Translation Summit IX: System Presentations",
month = sep # " 23-27",
year = "2003",
address = "New Orleans, USA",
url = "https://aclanthology.org/2003.mtsummit-systems.3",
abstract = "We describe a Chinese to English Machine Translation system developed at the Johns Hopkins University for the NIST 2003 MT evaluation. The system is based on a Weighted Finite State Transducer implementation of the alignment template translation model for statistical machine translation. The baseline MT system was trained using 100,000 sentence pairs selected from a static bitext training collection. Information retrieval techniques were then used to create specific training collections for each document to be translated. This document-specific training set included bitext and name entities that were then added to the baseline system by augmenting the library of alignment templates. We report translation performance of baseline and IR-based systems on two NIST MT evaluation test sets.",
}
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<abstract>We describe a Chinese to English Machine Translation system developed at the Johns Hopkins University for the NIST 2003 MT evaluation. The system is based on a Weighted Finite State Transducer implementation of the alignment template translation model for statistical machine translation. The baseline MT system was trained using 100,000 sentence pairs selected from a static bitext training collection. Information retrieval techniques were then used to create specific training collections for each document to be translated. This document-specific training set included bitext and name entities that were then added to the baseline system by augmenting the library of alignment templates. We report translation performance of baseline and IR-based systems on two NIST MT evaluation test sets.</abstract>
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%0 Conference Proceedings
%T The Johns Hopkins University 2003 Chinese-English machine translation system
%A Byrne, W.
%A Khudanpur, S.
%A Kim, W.
%A Kumar, S.
%A Pecina, P.
%A Virga, P.
%A Xu, P.
%A Yarowsky, D.
%S Proceedings of Machine Translation Summit IX: System Presentations
%D 2003
%8 sep 23 27
%C New Orleans, USA
%F byrne-etal-2003-johns
%X We describe a Chinese to English Machine Translation system developed at the Johns Hopkins University for the NIST 2003 MT evaluation. The system is based on a Weighted Finite State Transducer implementation of the alignment template translation model for statistical machine translation. The baseline MT system was trained using 100,000 sentence pairs selected from a static bitext training collection. Information retrieval techniques were then used to create specific training collections for each document to be translated. This document-specific training set included bitext and name entities that were then added to the baseline system by augmenting the library of alignment templates. We report translation performance of baseline and IR-based systems on two NIST MT evaluation test sets.
%U https://aclanthology.org/2003.mtsummit-systems.3
Markdown (Informal)
[The Johns Hopkins University 2003 Chinese-English machine translation system](https://aclanthology.org/2003.mtsummit-systems.3) (Byrne et al., MTSummit 2003)
ACL