To investigate to what extent noisy breaks are impeding the possible improvements from prosodically enriched models, we replaced all 4 and p breaks in the training and evaluation sets that did not align to the correct phrase boundaries as indicated by the treebank with break 1 for both the conversation sides and human-annotated sentences.
we conclude that, although the use of break indexes can indeed significantly improve performance over baseline models without them on conversation sides, tagging accuracy improves more by using smaller segments, for which the impact of the break indexes is marginal.