Multimodal Quality Estimation for Machine Translation
Shu Okabe, Frédéric Blain, Lucia Specia
Resources and Evaluation Short Paper
Session 2A: Jul 6
(08:00-09:00 GMT)
Session 3A: Jul 6
(12:00-13:00 GMT)
Abstract:
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.
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