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CUNI at WMT23 General Translation Task: MT and a Genetic Algorithm

Publication at Faculty of Mathematics and Physics |
2023

Abstract

This paper describes the submissions of different Charles University teams to WMT23 General translation task (English to Czech and Czech to Ukrainian translation directions). Our main submission, CUNI-GA, is a result of applying a novel n-best list reranking and modification method on translation candidates produced by the two other submitted systems, CUNI-Transformer and CUNI-DocTransformer (document-level translation only used for the $en \rightarrow cs$ direction).

Our method uses a genetic algorithm and MBR decoding to search for optimal translation under a given metric (in our case, a weighted combination of ChrF, BLEU, COMET22-DA, and COMET22-QE-DA). Based on the automatic metrics, our submissions are first in the constrained track and competitive with the best unconstrained systems according to some of the metrics.