2023
EMNLP
EMNLP 2023
HW-TSC’s Submissions to the WMT23 Discourse-Level Literary Translation Shared Task
Abstract
AbstractThis paper introduces HW-TSC’s submission to the WMT23 Discourse-Level Literary Translation shared task. We use standard sentence-level transformer as a baseline, and perform domain adaptation and discourse modeling to enhance discourse-level capabilities. Regarding domain adaptation, we employ Back-Translation, Forward-Translation and Data Diversification. For discourse modeling, we apply strategies such as Multi-resolutional Document-to-Document Translation and TrAining Data Augmentation.