CLAIMay 27, 2021

Multi-turn Dialog System on Single-turn Data in Medical Domain

arXiv:2105.12887v13 citations
Originality Synthesis-oriented
AI Analysis

This addresses the problem of data scarcity for medical dialog systems, but appears incremental as it adapts existing methods to a specific domain.

The paper tackles the challenge of building a multi-turn dialog system in the medical domain by leveraging verified single-turn QA pairs, as multi-turn conversational data is scarce and difficult to gather.

Recently there has been a huge interest in dialog systems. This interest has also been developed in the field of the medical domain where researchers are focusing on building a dialog system in the medical domain. This research is focused on the multi-turn dialog system trained on the multi-turn dialog data. It is difficult to gather a huge amount of multi-turn conversational data in the medical domain that is verified by professionals and can be trusted. However, there are several frequently asked questions (FAQs) or single-turn QA pairs that have information that is verified by the experts and can be used to build a multi-turn dialog system.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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