Coursera Corpus Mining and Multistage Fine-Tuning for Improving Lectures Translation
Table 8: BLEU scores in different iterations.
['A→AT→ATC', 'Ja→En', 'En→Ja']
Unfortunately, we do not see any improvement in translation quality. We can speculate the following two reasons. The dataset of approximately 40,000–45,000 sentences is too small to have any visible impact on translation quality. The best possible sentence alignments for Coursera data were already found, owing to our algorithm, similarity measure, and/or the initial MT system trained only on ASPEC and TED. Nevertheless, our observation does not necessarily hold for every language pair. We thus encourage researchers to try iterative refinement of training data in their own experimental settings.