2019 ACL ACL 2019

Apertium-fin-eng–Rule-based Shallow Machine Translation for WMT 2019 Shared Task

Abstract

AbstractIn this paper we describe a rule-based, bi-directional machine translation system for the Finnish—English language pair. The baseline system was based on the existing data of FinnWordNet, omorfi and apertium-eng. We have built the disambiguation, lexical selection and translation rules by hand. The dictionaries and rules have been developed based on the shared task data. We describe in this article the use of the shared task data as a kind of a test-driven development workflow in RBMT development and show that it suits perfectly to a modern software engineering continuous integration workflow of RBMT and yields big increases to BLEU scores with minimal effort.

🧭 Keyword Pioneer — rule-based machine translation
🐝 Cross-Pollinator — Artificial Intelligence, Data Science & Analytics, Deep Learning, Interdisciplinary, Machine Learning, Natural Language Processing, Speech & Audio
🌉 Interdisciplinary Bridge — Artificial Intelligence and Machine Learning and Natural Language Processing

Authors