文献类型：期刊文献

英文题名：Personalized Emotion Recognition and Emotion Prediction System Based on Cloud Computing

作者：Tian, Wenqiang[1]

第一作者：田文强

通讯作者：Tian, WQ[1]

机构：[1]Xinxiang Univ, Sch 3D Printing, Xinxiang 453003, Henan, Peoples R China

第一机构：新乡学院

通讯机构：[1]corresponding author), Xinxiang Univ, Sch 3D Printing, Xinxiang 453003, Henan, Peoples R China.|[11071]新乡学院;

年份：2021

卷号：2021

外文期刊名：MATHEMATICAL PROBLEMS IN ENGINEERING

收录：;EI(收录号：20212410494230);Scopus(收录号：2-s2.0-85107529302);WOS:【SCI-EXPANDED(收录号:WOS:000668995600002)】；

语种：英文

外文关键词：Cloud computing - Economic and social effects - Face recognition - Forecasting - Speech recognition - Support vector machines

摘要：Promoting economic development and improving people's quality of life have a lot to do with the continuous improvement of cloud computing technology and the rapid expansion of applications. Emotions play an important role in all aspects of human life. It is difficult to avoid the influence of inner emotions in people's behavior and deduction. This article mainly studies the personalized emotion recognition and emotion prediction system based on cloud computing. This paper proposes a method of intelligently identifying users' emotional states through the use of cloud computing. First, an emotional induction experiment is designed to induce the testers' positive, neutral, and negative three basic emotional states and collect cloud data and EEG under different emotional states. Then, the cloud data is processed and analyzed to extract emotional features. After that, this paper constructs a facial emotion prediction system based on cloud computing data model, which consists of face detection and facial emotion recognition. The system uses the SVM algorithm for face detection, uses the temporal feature algorithm for facial emotion analysis, and finally uses the classification method of machine learning to classify emotions, so as to realize the purpose of identifying the user's emotional state through cloud computing technology. Experimental data shows that the EEG signal emotion recognition method based on time domain features performs best has better generalization ability and is improved by 6.3% on the basis of traditional methods. The experimental results show that the personalized emotion recognition method based on cloud computing is more effective than traditional methods.