We build parallel FDA5 (ParFDA) Moses statistical machine translation (SMT) systems for all language pairs in the
workshop on statistical machine translation (Bojar et al., 2015) (WMT15) translation task and obtain results close to the top with an average of 3.176 BLEU points difference using significantly less resources for building SMT systems. ParFDA is a parallel implementation of feature decay algorithms (FDA) developed for fast deployment of accurate SMT systems. ParFDA Moses SMT system we built is able to obtain the top TER performance in French to English translation. We make the data for building ParFDA Moses SMT systems for WMT15 available:
\url{https://github.com/bicici/ParFDAWMT15}.
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Funders:
Science Foundation Ireland as part of the ADAPT research center (www.adaptcentre.ie, 07/CE/I1142) at Dublin City University, Science Foundation Ireland for the project “Monolingual and Bilingual Text Quality Judgments with Translation mance Prediction” (computing.dcu.ie/ ˜ebicici/Projects/TIDA_RTM.html, 13/TIDA/I2740).
ID Code:
20881
Deposited On:
29 Oct 2015 12:03 by
Mehmet Ergun Bicici
. Last Modified 22 Jul 2019 14:14