Our results indicate that the proposed utterance splitting applied to the training set greatly improves the neural model's accuracy and ability to generalize.
this can likely be attributed to the model having access to  table 6: Automatic metric scores of different models tested on the E2E dataset, both unmodified (s) and augmented (s) through the utterance splitting.