Improving Speech-Based Human Robot Interaction with Emotion Recognition
Improving Speech-Based Human Robot Interaction with Emotion Recognition
复制标题
通过情绪识别改善基于语音的人类机器人交互
DOI：
10.1007/978-3-319-25252-0_30
复制
发表时间：
2015
期刊：
影响因子：
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通讯作者：
Giuseppe Palestra
中科院分区：
文献类型：
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作者：
B. D. Carolis;S. Ferilli;Giuseppe Palestra
一些研究报告成功的结果如何社会辅助机器人可以作为辅助生活领域的接口。在这个领域，与机器人交互的一种自然方式是使用语音。然而，人类经常使用特殊的语调，可以改变句子的含义。出于这个原因，社会辅助机器人应该有能力通过对所讲句子的语言和声学分析的组合进行推理来识别话语的预期含义，以真正理解用户的反馈。我们开发了一个概率模型，该模型能够从其语言内容的分析和分类器的输出中推断出口语句子的预期含义，该分类器能够从数据集开始识别语音韵律的效价和唤醒。结果表明，结合语言内容和语音特征进行推理比仅使用语言成分进行推理效果更好。
Several studies report successful results on how social assistive robots can be employed as interface in the assisted living domain. In this domain, a natural way to interact with robots is to use a speech. However, humans often use particular intonation in the voice that can change the meaning of the sentence. For this reason, a social assistive robot should have the capability to recognize the intended meaning of the utterance by reasoning on the combination of linguistic and acoustic analysis of the spoken sentence to really understand the user’s feedback. We developed a probabilistic model that is able to infer the intended meaning of the spoken sentence from the analysis of its linguistic content and from the output of a classifier able to recognise the valence and arousal of the speech prosody starting from dataset. The results showed that reasoning on the combination of the linguistic content with acoustic features of the spoken sentence was better than using only the linguistic component.