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Humans often refer to personal narratives, life experiences, and events tomake a conversation more engaging and rich. While persona-grounded dialogmodels are able to generate responses that follow a given persona, they oftenmiss out on stating detailed experiences or events related to a persona, oftenleaving conversations shallow and dull. In this work, we equip dialog modelswith 'background stories' related to a persona by leveraging fictionalnarratives from existing story datasets (e.g. ROCStories). Since current dialogdatasets do not contain such narratives as responses, we perform anunsupervised adaptation of a retrieved story for generating a dialog responseusing a gradient-based rewriting technique. Our proposed method encourages thegenerated response to be fluent (i.e., highly likely) with the dialog history,minimally different from the retrieved story to preserve event ordering andconsistent with the original persona. We demonstrate that our method cangenerate responses that are more diverse, and are rated more engaging andhuman-like by human evaluators, compared to outputs from existing dialogmodels.

Unsupervised Enrichment of Persona-grounded Dialog with Background Stories