In everyday interactions, humans naturally exhibit behavioral cues, such as gaze and head movements, that signal their intentions while interpreting the behavioral cues of others to predict their intentions. Such intention prediction enables each partner to adapt their behaviors to the intent of others, serving a critical role in joint action where parties work together to achieve a common goal. Among behavioral cues, eye gaze is particularly important in understanding a person's attention and intention. In this work, we seek to (...) quantify how gaze patterns may indicate a person's intention. Our investigation was contextualized in a dyadic sandwich-making scenario in which a “worker” prepared a sandwich by adding ingredients requested by a “customer.” In this context, we investigated the extent to which the customers' gaze cues serve as predictors of which ingredients they intend to request. Predictive features were derived to represent characteristics of the customers' gaze patterns. We developed a support vector machine-based (SVM-based) model that achieved 76% accuracy in predicting the customers' intended requests based solely on gaze features. Moreover, the predictor made correct predictions approximately 1.8 s before the spoken request from the customer. We further analyzed several episodes of interactions from our data to develop a deeper understanding of the scenarios where our predictor succeeded and failed in making correct predictions. These analyses revealed additional gaze patterns that may be leveraged to improve intention prediction. This work highlights gaze cues as a significant resource for understanding human intentions and informs the design of real-time recognizers of user intention for intelligent systems, such as assistive robots and ubiquitous devices, that may enable more complex capabilities and improved user experience. (shrink)

Conversation is supported by the beliefs that people have in common and the perceptual experience that they share. The visual context of a conversation has two aspects: the information that is available to each conversant, and their beliefs about what is present for each other. In our experiment, we separated these factors for the first time and examined their impact on a spontaneous conversation. We manipulated the fact that a visual scene was shared or not and the belief that a (...) visual scene was shared or not. Participants watched videos of actors talking about a controversial topic, then discussed their own views while looking at either a blank screen or the actors. Each believed (correctly or not) that their partner was either looking at a blank screen or the same images. We recorded conversants’ eye movements, quantified how they were coordinated, and analyzed their speech patterns. Gaze coordination has been shown to be causally related to the knowledge people share before a conversation, and the information they later recall. Here, we found that both the presence of the visual scene, and beliefs about its presence for another, influenced language use and gaze coordination. (shrink)

The article is the first Russian translation of the most well-known piece in conversation analysis, written by the founders of CA Harvey Sacks, Emanuel Schegloff and Gail Jefferson. It has become a milestone in the development of the discipline. The authors offer a comprehensive approach to the study of conversational interactions. The approach is based on the analysis of detailed transcripts of the records of natural conversations. The authors show that in the course of the conversation co-conversationalists use a number (...) of techniques to organize the turn-taking. These techniques are combined in four rules: the first option is the transfer of speakership via allocation of the next speaker by the current speaker; if this first option is not realized, turn-taking may happen via the self-selection by one of the participants; if the second option remains unrealized too, the current speaker continues speaking, with all three options being recurrently provided at all next transition relevant places. The result of the operation of these rules is an orderly conversation based on the principle “one speaker at a time.” According to the authors, this model is compatible with obvious observations concerning conversational practices that they make. The authors show that in every conversation there is a turn-taking system in operation, which provides for a flexible adaptation of the every conversation’s structure to any possible topics and any possible speakers’ identities. Such approach considers how the participants in social interactions order their communication with each other, achieving a sense of normally occurring interaction. (shrink)