Multi-Domain Spoken Language Understanding Using Domain- and Task-Aware Parameterization
Table 3: Ablation Experiments on ASMixed datasets.
['Model', 'Overall Exact', 'Slot', 'Intent', 'ATIS Exact', 'SNIPS Exact']
In order to verify our claim that domain-aware parameterization can effectively capture domain-specific features. We remove the local syntax-aware encoder and conduct the experiment. We observe that the ATIS Exact acc drops 1.57% and SNIPS Exact acc drops 2.28%. In addition, the whole exact acc drops 1.98%, which shows that domain-specific feature extracted by local module is important for multi-domain SLU tasks, and domain-aware parameterization is better than only using the shared parameters for capturing domain-specific features.