Scalable and Accurate Dialogue State Tracking via Hierarchical Sequence Generation
Table 3: The joint goal accuracy of the DST models on the WoZ2.0 test set and the MultiWoZ test set. We also include the Inference Time Complexity (ITC) for each model as a metric for scalability. The baseline accuracy for the WoZ2.0 dataset is the Delexicalisation-Based (DB) Model Mrksic et al. (2017), while the baseline for the MultiWoZ dataset is taken from the official website of MultiWoZ Budzianowski et al. (2018).
['[BOLD] DST Models', '[BOLD] Joint Acc. WoZ 2.0', '[BOLD] Joint Acc. MultiWoZ', '[BOLD] ITC']
Table 3: The joint goal accuracy of the DST models on the WoZ2.0 test set and the MultiWoZ test set. We also include the Inference Time Complexity (ITC) for each model as a metric for scalability [CONTINUE] Table 3 compares our model with the previous state-of-the-art on both the WoZ2.0 test set and the MultiWoZ test set. For the WoZ2.0 dataset, we maintain performance at the level of the state-ofthe-art, with a marginal drop of 0.3% compared with previous work. Considering the fact that WoZ2.0 is a relatively small dataset, this small difference does not represent a significant big performance drop. On the muli-domain dataset, MultiWoZ, our model achieves a joint goal accuracy of 48.79%, which marginally outperforms the previous state-of-the-art.