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Multimodal Machine Translation
2021
IEEE Access
In recent years, neural network machine translation, especially in the field of multimodality, has developed rapidly. It has been widely used in natural languages processing tasks such as event detection and sentiment classification. The existing multimodal neural network machine translation is mostly based on the autoencoder framework of the attention mechanism, which further integrates spatial-visual features. However, due to the ubiquitous lack of corpus and the semantic interaction between
doi:10.1109/access.2021.3115135
fatcat:d2anaeg3qnarpfmlc4eap2urrm