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- W2897528489 abstract "Recent years have seen significant advances in natural language dialogue management and a growing recognition that multimodality can inform dialogue policies. A key dialogue policy problem is presented by 'no-match' scenarios, in which the dialogue system receives a user utterance for which no matching response is found. This paper reports on a study of the 'no-match' problem in the context of a dialogue agent embedded within a game-based learning environment. We investigate how users' facial expressions exhibited in response to the agent's no-match utterances predict the users' opinion of the agent after the interaction has completed. The results indicate that models incorporating users' facial expressions following no-match utterances are highly predictive of user opinion and significantly outperform baseline models. This work represents a key step toward affect-informed dialogue systems whose policies are informed by users' affective expression." @default.
- W2897528489 created "2018-10-26" @default.
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- W2897528489 date "2018-10-16" @default.
- W2897528489 modified "2023-10-12" @default.
- W2897528489 title "User Affect and No-Match Dialogue Scenarios" @default.
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- W2897528489 doi "https://doi.org/10.1145/3279972.3279979" @default.
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