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

WS 2016 Ozan CaglayanWalid AransaYaxing WangMarc MasanaMercedes García-MartínezFethi BougaresLoïc BarraultJoost van de Weijer

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... (read more)

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