Estimating Timing of Head Movements Based on the Volume and Pitch of Speech
Estimating Timing of Head Movements Based on the Volume and Pitch of Speech
复制标题
根据语音的音量和音调估计头部运动的时间
DOI：
10.1007/978-3-030-22649-7_26
复制
发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Nakayama Koichi
中科院分区：
文献类型：
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作者：
Yanagi Haruka;Oshima Chika;Nakayama Koichi
我们的研究目标是创造两个友好的交流机器人，与护理机构的老年人交谈。如果机器人的头部动作与老人同步，老人可能会对机器人做出积极的反应。然后，老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否是估计头部运动时间的有用数据。因为机器人需要实时移动他们的头，当其中一个机器人或人说话时，我们关注的是说话的音量和音调，而不是内容。此外，还明确了哪种机器学习方法可以创建合适的分类器模型来估计头部运动的时间。实验结果表明，随机森林分类器是最合适的分类方法。
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.
从语音中学习富有表现力的类人头部运动序列
DOI：
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发表时间：
2008
期刊：
影响因子：
--
作者：
C. Busso;Z. Deng;U. Neumann;Shrikanth S. Narayanan
通讯作者：
Shrikanth S. Narayanan