Personalized Dialogue Generation with Diversified Traits
Table 7. Manual evaluation with Fluency (Flu.) and Appropriateness (App.).
['Model', 'Flu.', 'App.']
Results Our model outperforms all our baselines significantly (t-test, p-value ¡ 0.05) in both metrics. This indicates that diversified personality traits help to generate more fluent and appropriate responses and our model can learn to incorporate proper personality traits in generated responses.