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Pitch pattern clustering of user utterances in human-machine dialogue

机译:人机对话中的用户话语的音高模式聚类

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The paper considers pitch pattern variations of user utterances in human-machine dialogue. For intelligent human-machine communication, it is essential that machines understand prosodic characteristics which imply a user's various attitude, emotion and intention beyond vocabulary. The authors' original focus is on particularly distinct pitch patterns and their roles in the actual dialogues. They used human-machine dialogues collected by a Wizard of OZ simulation. Many utterance segments belonged to clusters that were prosodically flat patterns. From the result, they considered that utterances which belonged to the other clusters and those which were far from the centroids included non-verbal information. In these utterances, there were talks to themselves and questions to the machine including emotional expressions of a puzzle or a surprise. These pitch patterns were not only rich in ups and downs, but also their slopes were upward, while the pitch patterns were generally even or a little downward. These results indicate that peculiar pitch period patterns show non-verbal expressions. In order to actually utilize such information on human-machine interactions, the representative pitch patterns should be investigated concerning their relationship to various types of communication.
机译:本文考虑了人机对话中的用户话语的音高模式变化。对于智能人机通信,机器必须了解韵律特征,这意味着用户的各种态度,情感和意图超越词汇。作者的原始重点是特别是在实际对话中特别明确的音高模式及其角色。他们使用了由OZ模拟的向导收集的人机对话。许多话语段属于群集是虚构的平面图案。从结果中,他们认为属于其他集群的话语和远离质心的话语包括非语言信息。在这些话语中,对自己的机器和问题进行了谈判,包括难题的情感表达或惊喜。这些俯仰模式不仅富有升压,而且它们的斜率向上,而俯仰模式通常均匀或略微向下。这些结果表明,特殊的俯仰周期模式显示出非言语表达。为了实际利用这些关于人机相互作用的信息,应研究其与各种类型的通信的关系来研究代表性的音调图案。

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