Computing a perfect metrics is as hard as the task itself, so lf course scores like BLEU and ROUGE use and easy approach instead that can be gamed. Every resear

Computing a perfect metrics is as hard as the task itself, so lf course scores like BLEU and ROUGE use and easy approach instead that can be gamed. Every researcher reading this kind of paper normally understands that. In this post, the 0 example for a good translation arise because the question is not formulated in the standard English way which use sujet/verb inversion. This problem is easily solved by extending the corpus with more diverse way to formulate questions. It’s also notable than the way a question would be translated in Chinese would also similarly be affected by the construct used by the MT system and the constructs present in the corpus. Instead of ditching the scores completely, improving the corpus seems to be a more productive approach, which would also benefit other researchers and the field in the long term.