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arXiv · 2304.00350

When Crowd Meets Persona: Creating a Large-Scale Open-Domain Persona Dialogue Corpus

Won Ik Cho·Yoon Kyung Lee·Seoyeon Bae·Jihwan Kim·Sangah Park·Moosung Kim·Sowon Hahn·Nam Soo Kim
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Abstract

Building a natural language dataset requires caution since word semantics is vulnerable to subtle text change or the definition of the annotated concept. Such a tendency can be seen in generative tasks like question-answering and dialogue generation and also in tasks that create a categorization-based corpus, like topic classification or sentiment analysis. Open-domain conversations involve two or more crowdworkers freely conversing about any topic, and collecting such data is particularly difficult for two reasons: 1) the dataset should be ``crafted" rather than ``obtained" due to privacy concerns, and 2) paid creation of such dialogues may differ from how crowdworkers behave in real-world settings. In this study, we tackle these issues when creating a large-scale open-domain persona dialogue corpus, where persona implies that the conversation is performed by several actors with a fixed persona and user-side workers from an unspecified crowd.

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Won Ik Cho, Yoon Kyung Lee, Seoyeon Bae, Jihwan Kim, Sangah Park, Moosung Kim, Sowon Hahn, Nam Soo Kim. 2023-04-01. When Crowd Meets Persona: Creating a Large-Scale Open-Domain Persona Dialogue Corpus. https://arxiv.org/abs/2304.00350

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