Can I read Towards Bidirectional Hierarchical Representations for Attention-Based Neural Machine Translation on EtoBox?

Towards Bidirectional Hierarchical Representations for Attention-Based Neural Machine Translation by Yang, Baosong; Wong, Derek F.; Xiao, Tong; Chao, Lidia S.; Zhu, Jingbo is a scholarly article available to read on EtoBox.

What is Towards Bidirectional Hierarchical Representations for Attention-Based Neural Machine Translation about?

This paper proposes a hierarchical attentional neural translation model which focuses on enhancing source-side hierarchical representations by covering both local and global semantic information using a bidirectional tree-based encoder. To maximize the predictive likelihood of target words, a weighted variant of an attention mechanism is used to balance the attentive information between lexical and phrase vectors. Using a tree-based rare word encoding, the proposed model is extended to sub-word level to alleviate the out-of-vocabulary (OOV) problem. Empirical results reveal that the proposed model significantly outperforms sequence-to-sequence attention-based and tree-based neural translation models in English-Chinese translation tasks.

Author

Yang, Baosong; Wong, Derek F.; Xiao, Tong; Chao, Lidia S.; Zhu, Jingbo

Published

2017

Language

EN