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Dialogue state tracking (DST) aims to extract essential information frommulti-turn dialogue situations and take appropriate actions. A belief state,one of the core pieces of information, refers to the subject and its specificcontent, and appears in the form of domain-slot-value. The trained modelpredicts "accumulated" belief states in every turn, and joint goal accuracy andslot accuracy are mainly used to evaluate the prediction; however, we specifythat the current evaluation metrics have a critical limitation when evaluatingbelief states accumulated as the dialogue proceeds, especially in the most usedMultiWOZ dataset. Additionally, we propose relative slot accuracy to complementexisting metrics. Relative slot accuracy does not depend on the number ofpredefined slots, and allows intuitive evaluation by assigning relative scoresaccording to the turn of each dialogue. This study also encourages not solelythe reporting of joint goal accuracy, but also various complementary metrics inDST tasks for the sake of a realistic evaluation.

Mismatch between Multi-turn Dialogue and its Evaluation Metric in Dialogue State Tracking