@inproceedings{tawfik2015adaptive,
author = {Tawfik, Ahmed and Zahran, Muhammad},
title = {Adaptive Tuning for Statistical Machine Translation (AdapT)},
booktitle = {International Conference on Intelligent Text Processing and Computational Linguistics},
year = {2015},
month = {April},
abstract = {In statistical machine translation systems, it is a common practice to use one set of weighting parameters in scoring the candidate translations from a source language to a target language. In this paper, we challenge the assumption that only one set of weights is sufficient to pick the best candidate translation for all source language sentences. We propose a new technique that generates a different set of weights for each input sentence. Our technique outperforms the popular tuning algorithm MERT on different datasets using different language pairs.},
url = {http://approjects.co.za/?big=en-us/research/publication/adaptive-tuning-for-statistical-machine-translation-adapt/},
}