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基于深度学习的心理情绪智能交互与反馈系统

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为了有效提高机器人的智能交互水平,设计一种基于深度学习的的心理情绪智能交互系统.通过分离卷积实现深度学习,对人的面部表情(喜悦、伤心、气愤、恐惧等)进行分析和特征提取,实验结果显示训练后的模型对面部表情测试集的识别准确率可达71.1%.系统分别设计了与6种不同面部表情向对应的NAO机器人肢体动作,实验结果表明,机器人可在2 s内完成识别并进行动作反馈,且连续10帧的识别结果较为准确.
Intelligent Interaction and Feedback System of Psychology and Emotion Based on Deep Learning
In order to effectively improve the intelligent interaction of robot,an intelligent interaction and feedback system of psychology and emotion based on deep learning is proposed.Deep learning is realized by separating convolution,and human fa-cial expressions(joy,sadness,anger,fear,etc.)are analyzed and these features are extracted.The experimental results show that the recognition accuracy of the trained model face expression test set can reach 71.1%.The limb movements of NAO robot corresponding to six different facial expressions are designed,respectively.The experimental results show that the robot can complete the recognition and action feedback within 2 s,and the recognition results of 10 consecutive frames are more accurate.

deep learningpsychology and emotionintelligent interaction and feedback systemrobotfacial expression

张成玉

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西安医学院,学生工作部(学生处)、武装部,陕西,西安 710021

深度学习 心理情绪 智能交互与反馈系统 机器人 面部表情

陕西省教育科学规划课题(十三五)(2020)

SGH20Y1458

2024

微型电脑应用
上海市微型电脑应用学会

微型电脑应用

CSTPCD
影响因子:0.359
ISSN:1007-757X
年,卷(期):2024.40(2)
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