Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems
Table 4: Zero-shot experiments on an unseen domain. In taxi domain, our model achieves 60.58% joint goal accuracy without training on any samples from taxi domain. Trained Single column is the results achieved by training on 100% single-domain data as a reference.
['[EMPTY]', '[BOLD] Trained Single  [ITALIC] Joint', '[BOLD] Trained Single  [ITALIC] Slot', '[BOLD] Zero-Shot  [ITALIC] Joint', '[BOLD] Zero-Shot  [ITALIC] Slot']
S4SS3SSS0Px2 Zero-shot We run zero-shot experiments by excluding one domain from the training set. Although performances on the other zero-shot domains are not especially promising, they still achieve around 50 to 65% slot accuracy without using any in-domain samples. The reason why the zero-shot performance on the taxi domain is high is because all four slots share similar values with the corresponding slots in the train domain.