Hierarchical Multi-Label Dialog Act Recognition on Spanish Data
Table 6: Level 1 accuracy results on user and system segments.
['[BOLD] Speaker', '[BOLD] Accuracy  [ITALIC] m', '[BOLD] Accuracy  [ITALIC] s']
When information from three preceding segments is used, the classifier only fails to accurately predict two percent of the segments. That result takes into account all the segments in the DIHANA Corpus. However, the system segments are scripted and, thus, are easier to predict than the user segments. In fact, if we consider the scenario of a dialog system trying to predict dialog acts, it is aware of its own and must only predict those of its conversational partners. As expected, the average accuracy on system segments is 99.91%. On user segments that value decreases to 95.17%, which still reveals high performance.