A Recurrent Neural Networks Approach for Estimating the Quality of Machine Translation Output
Hyun Woo Kim, Jong-Hyeok Lee · 2016
This paper presents a novel approach using recurrent neural networks for estimating the quality of machine translation output.A sequence of vectors made by the prediction method is used as the input of the final recurrent neural network.The prediction method uses bi-directional recurrent neural network architecture both on source and target sentence to fully utilize the bi-directional quality information from source and target sentence.Our experiments show that the proposed recurrent neural networks approach achieves a performance comparable to the existing stateof-the-art models for estimating the sentencelevel quality of English-to-Spanish translation.