METHOD AND DEVICE FOR TRAINING NEURAL MACHINE TRANSLATION MODEL FOR IMPROVED TRANSLATION PERFORMANCE

摘要

A method and a device for training a neural machine translation model to ensure high translation performance even in a language pair or a domain having a small amount of parallel corpora and solving the problems of over-translation and under-translation caused by the inaccuracy of word-alignment information of an attention network. To this end, bidirectional neural machine translation models are built, and single language corpora are made available for training on the basis of symmetric relation between the models. Also, incomplete alignment information between attention networks of the bidirectional neural machine translation models is normalized to have orthogonal relation so that accurate alignment information may be learned.