Table 4 shows that the models trained on MuST-C data achieve better results on the balanced test set in all the three tasks.
: i) a reduction of 10.1 WER points in ASR indicates a higher quality of audio-transcription alignments, ii) a BLEU increase of 0.56 points in MT indicates a similar quality for transcription-translation alignments, and iii) a BLEU increase of 3.31 points in SLT indicates a higher quality of audio-translation alignments.