2022 EMNLP EMNLP 2022

PROMT Systems for WMT22 General Translation Task

Abstract

AbstractThe PROMT systems are trained with the MarianNMT toolkit. All systems use the transformer-big configuration. We use BPE for text encoding, the vocabulary sizes vary from 24k to 32k for different language pairs. All systems are unconstrained. We use all data provided by the WMT organizers, all publicly available data and some private data. We participate in four directions: English-Russian, English-German and German-English, Ukrainian-English.

🐝 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, Speech & Audio