Alternating Roles Dialog Model with Large-Scale Pre-Trained Language Models
Table 2: Results on MultiWOZ. Supervision denotes whether a model leverages dialog state or/and dialog act annotations. All models use the ground truth dialog state for database search. ARDM without supervision from annotation can still achieve comparable results.
['Model', 'Supervision Dialog State', 'Supervision Dialog Act', 'Inform (%)', 'Success (%)', 'BLEU-4']
Without any supervision from dialog states or dialog acts, ARDM significantly outperforms the MultiWOZ Baseline and LaRL on BLEU-4 and Inform rate, and is on par with HDSA. However, HDSA uses dialog act supervision and a large pretrained language model, BERT. Our model requires no annotation and can achieve similar results. This suggests our speaker role modeling and large-scale pre-training methods work similarly as the useful dialog act annotations. All the results show that our method’s excellent performance remains consistent in multi-domain dialogs.