Effective Data Augmentation Approaches to End-to-End Task-Oriented Dialogue
TABLE III: Analysis on the Precision and Recall.
['[EMPTY]', 'CamRest676 Success F1', 'CamRest676 Precision', 'CamRest676 Recall', 'CamRest676 TP', 'CamRest676 FP', 'CamRest676 FN']
Obviously, our method can significantly improve the recall by nearly 9 points while keeping the precision basically the same as the baseline. The reason behind the improvement of the recall is that the proposed methods substantially increases TP and decreases FN. This is because the diversity in user utterances created by data augmentation helps the dialogue system recognize more requested slots and further allows the decoder to answer these slots in machine responses. Without data augmentation, some slots are just not detected at all in the baseline (thus a higher FN).