Comparing Multilingual NMT Models and Pivoting

Abstract

Following recent advancements in multilingual machine translation at scale, our team carried out tests to compare the performance of multilingual models (M2M from Facebook and multilingual models from Helsinki-NLP) with a two-step translation process using English as a pivot language. Direct assessment by linguists rated translations produced by pivoting as consistently better than those obtained from multilingual models of similar size, while automated evaluation with COMET suggested relative performance was strongly impacted by domain and language family.

Tasks

Reproductions