Sparse Text Generation
Table 7: Human evaluation of dialogue generation. All scores marked in bold at each column outperform the non-bold ones with statistical significance, according to the Wilcoxon’s test with p-value <0.05.
['[EMPTY]', 'Fluency', 'Consistency', 'Engagement']
Finally, we performed human evaluation following the ConvAI2 challenge: 6 volunteers had 30 conversations each with models using the different sampling methods. The volunteers scored the conversations from 1 to 5 in terms of fluency, consistency (whether the model’s utterances are coherent with their persona and the model does not contradict itself), and engagement. The model’s personas were randomly selected from the PersonaChat validation set.