CUNI Systems for the WMT 22 C zech- U krainian Translation Task (2022)

Abstract: We present Charles University submissions to the WMT 22 GeneralTranslation Shared Task on Czech-Ukrainian and Ukrainian-Czech machine translation. We present two constrained submissions based on block back-translation and tagged back-translation and experiment with rule-basedromanization of Ukrainian. Our results show that the romanization onlyhas a minor effect on the translation quality. Further, we describe Charles Translator,a system that was developed in March 2022 as a response to the migrationfrom Ukraine to the Czech Republic. Compared to our constrained systems,it did not use the romanization and used some proprietary data sources.

## introduction how fast can the machine translation (mt) community react to a sudden need of a high-quality mt system which was previously under low demand? this question motivated the new task at the wmt this year, which is czech-ukrainian translation. both languages belong to the slavic language family (czech is western slavic, ukrainian is eastern slavic), and share some lexical and structural characteristics. unlike czech, which uses the latin script, ukrainian uses its variant of the cyrillic alphabet. we submit three systems to the wmt 22 general translation shared task for this language pair in each translation direction. the first system, cuni-jl-jh, implemented in marian @xcite , uses tagged back-translation and is a result of our experiments with romanization of ukrainian. our second system, cuni-transformer, implemented in ten-sor2tensor @xcite , uses block backtranslation. finally, we submit an unconstrained system, charles translator, implemented in tensor2tensor, which has been developed in * the author order was determined by a coin toss. ## constrained wmt submissions we submitted two systems in each translation direction that use the same parallel and monolingual data, but different techniques and different toolkits. this section first describes the shared data processing steps and then the specifics of each of the submissions in separate subsections. ## charles translator for ukraine charles translator for ukraine is a free czech-ukrainian online translation service available for public at https://translator.cuni.cz and as an android app. it was developed at charles university in march 2022 to help refugees from ukraine by narrowing the communication gap between them and other people in czechia. similarly to cuni-transformer, it is based on transformer and iterated block back-translation @xcite . the training used source-side artificial noising, but no romanization and no inline casing. it was trained on most (but not all) of the training data provided by wmt plus about one million uk-cs sentences from the intercorp v14 corpus @xcite , so this submission is unconstrained. ## results in this section, we report bleu scores on the flores 101 development set that we used to make our decisions about the system development and the final automatic scores. note that the validation set is very different from the test set. the validation set consists of clean and rather complicated sentences from wikipedia articles, whereas the wmt 22 test set is noisy user-generated text from the logs of the production deployment of charles translator. foot_4 tagged bt systems. results on wmt test. automatic evaluation on the wmt22 test set is presented in ## conclusions we presented charles university submissions to the wmt 22 general and used some proprietary data sources. our results show that the romanization only has a minor effect on the translation quality, compared to machine-learning aspects that affect translation quality. block back-translation seems to deliver slightly better results that tagged back-translation, however the differences are only small.