Real Time Smart Music Player Using Facial Expression

Natha Harika, T. Kumar
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Abstract

According to the World Happiness Report 2021, created by the World Happiness Council, it has ranked 140 countries based on how satisfied their citizens are. Due to COVID-19 pandemic, they observed there was large decline in mental health because of unemployment and decrease inperson gatherings resulting in a decrease in the happiness index of countries. Therefore, in this work we targeted to improve the emotional state of the person and make him happy, by recognizing the persons emotion and plays corresponding music will help user in changing their mood. Music's magical power has been scientifically established and people enjoy listening to music that reflects their emotional feelings, it is a stress-relieving tool and has the ability to control a wide range of psychological states. We used Viola Jones algorithm, Data augmentation and CoAtNet algorithm to detect the emotion of a person. A high accuracy is achieved with proposed CoAtNet model when compared to other methods like Conventional CNN, Principal Component Analysis (PCA) and SVM etc. We have also deployed the model on the STM32H747I Board.
使用面部表情的实时智能音乐播放器
根据世界幸福理事会发布的《2021年世界幸福报告》,该报告根据各国公民的幸福程度对140个国家进行了排名。他们观察到,由于新冠肺炎大流行,失业和面对面聚会的减少导致各国的幸福指数下降,导致心理健康大幅下降。因此,在这个作品中,我们的目标是改善人的情绪状态,让他快乐,通过识别人的情绪并播放相应的音乐来帮助用户改变他们的情绪。音乐的神奇力量已经被科学地证实,人们喜欢听反映他们情绪感受的音乐,它是一种缓解压力的工具,有能力控制广泛的心理状态。我们使用Viola Jones算法、Data augmentation和CoAtNet算法来检测一个人的情绪。与传统的CNN、主成分分析(PCA)和支持向量机(SVM)等方法相比,本文提出的CoAtNet模型具有较高的准确率。我们还将该模型部署在STM32H747I板上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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