Table 7 shows that, using only non-prosodic features (ASR, SYS, POS), corrections can still be predicted with an accuracy statistically equivalent to our best results.
using all feature types (PROS+ASR+SYS+POS, DIA = all, error = 16.38%) is equivalent to using only non-prosodic features (ASR+SYS+POS, DIA = all, error = 17.01%).