Exploiting Persona Information for Diverse Generation of Conversational Responses
Table 4: Pairwise preference of three persona-based models (N=5).
['[BOLD] Pref. (%)', 'Per.-Seq2Seq', 'GPMN', 'Per.-CVAE']
In addition, we performed a Preference Test in three persona-based models. In this setting, the judges are presented with pairwise items and are asked to decide which of the two N responses is of higher quality. And a partial ordering relation about the overall quality is given: best response quality > response variety > persona coverage. The judges first need to do a re-rank in mind and decide which model offers a better top response. If no difference then considering variety in responses, otherwise whether persona text is expressed. In the pairwise setting, the diverse persona-based responses are more attractive to users.