2020
ACL
ACL 2020
Multimodal Quality Estimation for Machine Translation
Abstract
AbstractWe 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.
🌉
Interdisciplinary Bridge
— Artificial Intelligence and Natural Language Processing
🐝
Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Speech & Audio
Authors
Topics
Artificial Intelligence > Core AI > Multimodal Learning
Natural Language Processing > Applications > Machine Translation
Computer Vision > Core AI > Multimodal Learning
Machine Learning > Learning Types > Multi-Modal Learning
Deep Learning > Learning Types > Multi-Modal Learning
Deep Learning > Learning Types > Multimodal Learning