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Estimating Timing of Head Movements Based on the Volume and Pitch of Speech

机译:基于音量和音高的音量估计头部运动的时序

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Our research aims to create two friendly communication robots to talk with elderly people in nursing facilities. If the robots synchronize their head movements in response to the elderly person, the elderly person may react favorably to the robot. Then, the elderly person can enjoy talking with these two robots. In this paper, we investigated whether the volume and pitch of the speech are useful data for estimating the timing of head movements. Because the robots need to move their heads in real time, when one of the robots or the person is talking, we focus on the volume and pitch of the speech, not the content. Moreover, it was cleared which machine learning method creates suitable classifier models for estimating the timing of head movements. The experimental results showed that Random Forest classifier was the most suitable method.
机译:我们的研究旨在创造两个友好的沟通机器人,与老年人谈话。如果机器人同步他们的头部运动响应老年人,则老年人可能对机器人有利反应。然后,老年人可以享受与这两个机器人交谈。在本文中,我们研究了语音的音量和音高是有用的,用于估计头部运动的定时。因为机器人需要实时移动他们的头,当一个机器人或者人交谈时,我们专注于演讲的音量和音高,而不是内容。此外,清除了哪种机器学习方法创建合适的分类器模型,用于估计头部运动的定时。实验结果表明,随机林分类器是最合适的方法。

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