Findings of the WMT 2022 Shared Task on Translation Suggestion
This work addresses the need for improving machine translation outputs by offering specific suggestions, but it is incremental as it builds on existing shared task frameworks without introducing new methods.
The paper tackled the problem of providing alternative words or phrases for machine-translated documents by introducing the first WMT shared task on Translation Suggestion, which included two sub-tasks with different levels of hint provision, and reported results from 92 submissions for English-German and English-Chinese language pairs using BLEU as the evaluation metric.
We report the result of the first edition of the WMT shared task on Translation Suggestion (TS). The task aims to provide alternatives for specific words or phrases given the entire documents generated by machine translation (MT). It consists two sub-tasks, namely, the naive translation suggestion and translation suggestion with hints. The main difference is that some hints are provided in sub-task two, therefore, it is easier for the model to generate more accurate suggestions. For sub-task one, we provide the corpus for the language pairs English-German and English-Chinese. And only English-Chinese corpus is provided for the sub-task two. We received 92 submissions from 5 participating teams in sub-task one and 6 submissions for the sub-task 2, most of them covering all of the translation directions. We used the automatic metric BLEU for evaluating the performance of each submission.