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- W4226330303 abstract "Turn-taking is an important attribute of conversation. Non-verbal behavior is very important for analyzing the turn-taking in multi-party conversation. In this study, we focused on the gaze behavior and improved the framework for predicting turn by analyzing the gaze transition patterns in a four-participant conversation. We define a set of gaze labels for the changes in the gaze of the speaker and the listener, and then encode them into different patterns. We also give an effective predictive model based on Naïve Bayes classifier for predicting turn shift. Experimental results show that our framework performs better than previous works." @default.
- W4226330303 created "2022-05-05" @default.
- W4226330303 creator A5075216385 @default.
- W4226330303 date "2021-12-22" @default.
- W4226330303 modified "2023-10-16" @default.
- W4226330303 title "Improved Gazing Transition Patterns for Predicting Turn-Taking in Multiparty Conversation" @default.
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- W4226330303 doi "https://doi.org/10.1145/3511176.3511208" @default.
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