Deep Reinforcement Learning For Modeling Chit-Chat Dialog With Discrete Attributes
Table 4: Validation Perplexity for the Open-Subtitles dataset.
['Model', 'Num Dialogs(in Millions) Attributes', 'Num Dialogs(in Millions) 0.2 M', 'Num Dialogs(in Millions) 0.5 M', 'Num Dialogs(in Millions) 1 M', 'Num Dialogs(in Millions) 2 M']
In most of the cases, we observe that the conditioning with acts from both the frames and switchboard yields the lowest perplexity. We observe that the perplexity improvement is substantial for smaller datasets which is also corroborated from the experiments with the Reddit dataset.