%0 Conference Proceedings %T Multimodal Quality Estimation for Machine Translation %A Okabe, Shu %A Blain, Frédéric %A Specia, Lucia %Y Jurafsky, Dan %Y Chai, Joyce %Y Schluter, Natalie %Y Tetreault, Joel %S Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics %D 2020 %8 July %I Association for Computational Linguistics %C Online %F okabe-etal-2020-multimodal %X We propose approaches to Quality Estimation (QE) for Machine Translation that explore both text and visual modalities for Multimodal QE. We compare various multimodality integration and fusion strategies. For both sentence-level and document-level predictions, we show that state-of-the-art neural and feature-based QE frameworks obtain better results when using the additional modality. %R 10.18653/v1/2020.acl-main.114 %U https://aclanthology.org/2020.acl-main.114 %U https://doi.org/10.18653/v1/2020.acl-main.114 %P 1233-1240