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Turn-alignment using eye-gaze and speech in conversational interaction

机译:在对话互动中使用视线和语音进行转身对准

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Spoken interactions are known for accurate timing and alignment between interlocutors: turn-taking and topic flow are managed in a manner that provides conversational fluency and smooth progress of the task. This paper studies the relation between the interlocutors' eye-gaze and spoken utterances, and describes our experiments on turn alignment. We conducted classification experiments by Support Vector Machine on turn-taking using the features for dialogue act, eye-gaze, and speech prosody in conversation data. As a result, we demonstrated that eye-gaze features are important signals in turn management, and seem even more important than speech features when the intention of utterances is clear.
机译:语音交互以对话者之间的准确时间安排和对齐而著称:轮流进行和话题流以提供会话流畅性和任务顺利进行的方式进行管理。本文研究了对话者的目光与语音之间的关系,并描述了我们在转弯对准中的实验。我们使用对话数据,对话注视和语音韵律等功能,通过支持向量机对转弯进行了分类实验。结果,我们证明了注视特征是转弯管理中的重要信号,并且当发声的意图明确时,注视特征似乎甚至比语音特征更重要。

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