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Exploring Interactive Teaching of a Multi-Modal Emotional Expression of a Humanoid Robot

机译:探索人形机器人多模态情绪表达的互动教学

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One of the most popular domains in the current research is getting robots to replace humans in the difficult and dangerous tasks. To do that a robot must act as intelligently as humans towards different problems. Giving life to a robot is a dream that is coming true. One Of the hottest fields in this domain is teaching the robot how to understand and express emotions. The main target of this paper is to present an approach to teach a humanoid how to understand and then to express emotions. The robot should be able to understand emotions from plain text, voice and facial expressions then express them using gestures and voices. To validate the results, the robot should be able to read a text, understand the emotions in this text and then express them. Text synthesis is implemented through machine learning while expressing emotions is done through analyzing and then imitating people's voices and postures while they experience different emotions. This research only focuses on the basic 3 emotions: happiness, sadness and anger. For the results an accuracy of 73.9% was reached in text synthesis, and survey was done to test the clarity of emotions expressed by the robot. An accuracy of 83.6%, 87.6% and 86.3% was reached in expressing happiness, sadness and anger respectively.
机译:目前研究中最受欢迎的域之一是让机器人在困难和危险的任务中取代人类。要做到一个机器人必须像人类一样智能地行动不同的问题。给机器人的生活是一个梦想的梦想。这个域名的最热门领域是教授机器人如何理解和表达情绪。本文的主要目标是提出一种教导人形的方法,如何理解,然后表达情绪。机器人应该能够了解纯文本,语音和面部表情的情绪,然后使用手势和声音来表达它们。为了验证结果,机器人应该能够阅读文本,了解本文中的情绪,然后表达它们。文本综合通过机器学习实施,同时表达情绪是通过分析来完成的,然后在他们体验不同的情绪时模仿人们的声音和姿势。这项研究仅关注基本的3情绪:幸福,悲伤和愤怒。对于结果,在文本综合中达到了73.9%的准确性,并进行了调查以测试机器人表达的情绪清晰度。在表达幸福,悲伤和愤怒时,达到了83.6%,87.6%和86.3%的准确性。

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