To conquer the problems described above, we propose a multi-task learning framework based on a sequence learning model to conduct machine translation from one source language to multiple target languages, inspired by the recently proposed neural machine translation(NMT) framework proposed by .
we extend the recurrent neural network based encoder-decoder framework to a multi-task learning model that shares an encoder across all language pairs and utilize a different decoder for each target language.