Using Respiration to Predict Who Will Speak Next and When in Multiparty Meetings

Techniques that use nonverbal behaviors to predict turn-changing situations—such as, in multiparty meetings, who the next speaker will be and when the next utterance will occur—have been receiving a lot of attention in recent research. To build a model for predicting these behaviors we conducted a r...

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Veröffentlicht in:ACM transactions on interactive intelligent systems 2016-08, Vol.6 (2), p.1-20
Hauptverfasser: Ishii, Ryo, Otsuka, Kazuhiro, Kumano, Shiro, Yamato, Junji
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creator Ishii, Ryo
Otsuka, Kazuhiro
Kumano, Shiro
Yamato, Junji
description Techniques that use nonverbal behaviors to predict turn-changing situations—such as, in multiparty meetings, who the next speaker will be and when the next utterance will occur—have been receiving a lot of attention in recent research. To build a model for predicting these behaviors we conducted a research study to determine whether respiration could be effectively used as a basis for the prediction. Results of analyses of utterance and respiration data collected from participants in multiparty meetings reveal that the speaker takes a breath more quickly and deeply after the end of an utterance in turn-keeping than in turn-changing. They also indicate that the listener who will be the next speaker takes a bigger breath more quickly and deeply in turn-changing than the other listeners. On the basis of these results, we constructed and evaluated models for predicting the next speaker and the time of the next utterance in multiparty meetings. The results of the evaluation suggest that the characteristics of the speaker's inhalation right after an utterance unit—the points in time at which the inhalation starts and ends after the end of the utterance unit and the amplitude, slope, and duration of the inhalation phase—are effective for predicting the next speaker in multiparty meetings. They further suggest that the characteristics of listeners' inhalation—the points in time at which the inhalation starts and ends after the end of the utterance unit and the minimum and maximum inspiration, amplitude, and slope of the inhalation phase—are effective for predicting the next speaker. The start time and end time of the next speaker's inhalation are also useful for predicting the time of the next utterance in turn-changing.
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