A Retrieval-based Approach to Goal-Oriented Dialogue
Table 2: Inform/request results divided into two section. The top models do not make use of any past dialog acts to condition the decoder to generate a response. The models at the bottom use dialog acts, and belief state in order to generate better responses
['[EMPTY]', 'Model', 'Inform', 'Request', 'BLEU']
As we are concerned with improving dialogue generation for goal oriented dialogue, we are interested in assessing how our simple approach compares to models explicitly using dialog acts as extra information. We compute the inform/request accuracy and compare to the state-of-the-art Chen et al. present experiments conditioning both on predicted acts as well as ground truth past acts. We divide the results into models using act information to condition the language generation and models that do not.