@article{7dc9871f-04e4-4763-8466-3b00e53b3375,
author = {Ameur Douib, David Langlois, Kamel Smaïli},
title = {A Translation Evaluation Function based on Neural Network},
journal = {Schedae Informaticae},
volume = {2016},
number = {Volume 25},
year = {2017},
issn = {1732-3916},
pages = {139-151},keywords = {Statistical Machine Translation; Genetic algorithm; Quality estimation; Neural network},
abstract = {In this paper, we study the feasibility of using a neural network to learn a fitness function for a machine translation system based on a genetic algorithm termed GAMaT. The neural network is learned on  features extracted from pairs of source sentences and their translations. The fitness function is trained in order to estimate the BLEU of a translation as precisely as possible. The estimator has been trained on a corpus of more than 1.3 million data. The performance is very promising: the difference between the real BLEU and the one given by the estimator is equal to 0.12 in terms of Mean Absolute Error.},
doi = {10.4467/20838476SI.16.011.6192},
url = {https://ejournals.eu/en/journal/schedae-informaticae/article/a-translation-evaluation-function-based-on-neural-network}
}