Asynchronous and Segmented Bidirectional Encoding for NMT

arXiv:2402.14849v1 Announce Type: cross
Abstract: With the rapid advancement of Neural Machine Translation (NMT), enhancing translation efficiency and quality has become a focal point of research. Despite the commendable performance of general models such as the Transformer in various aspects, they still fall short in processing long sentences and fully leveraging bidirectional contextual information. This paper introduces an improved model based on the Transformer, implementing an asynchronous and segmented bidirectional decoding strategy aimed at elevating translation efficiency and accuracy. Compared …

abstract advancement arxiv asynchronous become cs.ai cs.cl cs.lg efficiency encoding general machine machine translation neural machine translation performance processing quality research transformer translation type