Multi-Domain Dialogue Acts and Response Co-Generation
Table 3: Results of different act generation methods, where BiLSTM, Word-CNN and Transformer are baselines from Chen et al. (2019). MarCo is our act generator trained jointly with the response generator and Transformer (GEN) is that without joint training.
['Method', 'F1']
To evaluate the performance of our act generator, we compare it with several baseline methods mentioned in Chen et al. We use MarCo to represent our act generator which is trained jointly with the response generator, and use Transformer (GEN) to denote our act generator without joint training. But after trained jointly with the response generator, MarCo manages to show the best performance, confirming the effect of the co-generation.