Does Multimodality Help Human and Machine for Translation and Image Captioning?

WMT, 2016.

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Abstract:

This paper presents the systems developed by LIUM and CVC for the WMT16 Multimodal Machine Translation challenge. We explored various comparative methods, namely phrase-based systems and attentional recurrent neural networks models trained using monomodal or multimodal data. We also performed a human evaluation in order to estimate the us...More

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