Neural Belief Tracker: Data-Driven Dialogue State Tracking
Table 1: DSTC2 and WOZ 2.0 test set accuracies for: a) joint goals; and b) turn-level requests. The asterisk indicates statistically significant improvement over the baseline trackers (paired t-test; p<0.05).
['[BOLD] DST Model', '[BOLD] DSTC2  [BOLD] Goals', '[BOLD] DSTC2  [BOLD] Requests', '[BOLD] WOZ 2.0  [BOLD] Goals', '[BOLD] WOZ 2.0  [BOLD] Requests']
The NBT models outperformed the baseline models in terms of both joint goal and request accuracies. For goals, the gains are always statistically significant (paired t-test, p<0.05). Moreover, there was no statistically significant variation between the NBT and the lexicon-supplemented models, showing that the NBT can handle semantic relations which otherwise had to be explicitly encoded in semantic dictionaries.