CoVoST: A Diverse Multilingual Speech-To-Text Translation Corpus
Table 4: BLEU scores for MT models.
['[EMPTY]', 'CoVoST Test', 'TT']
MT models take transcripts (without punctuation) as inputs and outputs translations (with punctuation). For simplicity, we do not change the text preprocessing methods for MT to correct this mismatch. Moreover, this mismatch also exists in cascading ST systems, where MT model inputs are the outputs of an ASR model. We notice that the results are consistent with what we see from ASR models. For example thanks to abundant training data, French has a decent BLEU score of 29.8/25.4. German doesn’t perform well, because of less richness of content (transcripts). The other languages are relatively low resource in CoVoST and it is difficult to train decent models without additional data or pre-training techniques.