Who Said That? Selecting the Correct Persona from Conversational Text

PROCEEDINGS OF THE 23RD ACM INTERNATIONAL CONFERENCE ON INTELLIGENT VIRTUAL AGENTS, IVA 2023(2023)

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摘要
In this paper, we explore the ability to detect personas from conversational data. First, we adapt the Persona-Chat dataset, a wellknown dialogue dataset, to support the task of selecting the correct persona out of various candidates. Then, we introduce persona perturbations to create additional identical personas that act as more challenging distractors. We train three different BERT-based models in a multiple-choice fashion to select the correct persona from a group of distractor personas. We show that this approach is able to discern between the group of original persona candidates, however, these models struggle to maintain high performance when we employ very identical distractors obtained from the proposed perturbations.
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persona detection,personalized agents,dialogue dataset
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