Joint Training for Neural Machine Translation 1st Edition by Yong Cheng ISBN 9813297484 9789813297487
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Product details:
ISBN 10: 9813297484
ISBN 13: 9789813297487
Author: Yong Cheng
This book presents four approaches to jointly training bidirectional neural machine translation (NMT) models. First, in order to improve the accuracy of the attention mechanism, it proposes an agreement-based joint training approach to help the two complementary models agree on word alignment matrices for the same training data. Second, it presents a semi-supervised approach that uses an autoencoder to reconstruct monolingual corpora, so as to incorporate these corpora into neural machine translation. It then introduces a joint training algorithm for pivot-based neural machine translation, which can be used to mitigate the data scarcity problem. Lastly it describes an end-to-end bidirectional NMT model to connect the source-to-target and target-to-source translation models, allowing the interaction of parameters between these two directional models.
Table of contents:
Chapter 1. Neural Machine Translation
Chapter 2. Agreement-Based Joint Training for Bidirectional Attention-Based Neural Machine Translation
Chapter 3. Semi-supervised Learning for Neural Machine Translation
Chapter 4. Joint Training for Pivot-Based Neural Machine Translation
Chapter 5. Joint Modeling for Bidirectional Neural Machine Translation with Contrastive Learning
Chapter 6. Related Work
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Tags: Yong Cheng, Joint, Training, Neural, Machine, Translation
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