Recommendation of Music Based on Facial Emotion using Machine Learning Technique

Advances in Computational Intelligence in Materials Science Pub Date : 2023-06-07 DOI:10.53759/acims/978-9914-9946-9-8_16

S. G, Evangelin Blessy A, Jeya Aravinth S, Vignesh Prabhu M, VijayaSarathy R

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Abstract

Music plays a vital role in human life, and it is a valid therapy to potentially reduce depression, anxiety, as well as to improve mood, self-esteem, and quality of life. Music has the power to change human emotion as expressed through facial expression. It’s a difficult task to recommend music based on emotion. The existing system on emotion recognition and music recommendation is focused on depression and mental health analysis. Hence a model is proposed to recommend music based on recognition of face expression to improve or change the emotion. Face emotion recognition (FER) is implemented using YoloV5 algorithm. The output of FER is a type of emotion classified as happy, anger, sad, and neutral which is the input to music recommendation system. A Music player is created to keep track of the user’s favorite based on the emotion. If the user is new to the system, then generalized music will be suggested. The aim of the paper is to recommend music to the user according to their emotion to further improve it.

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基于面部情感的机器学习音乐推荐

音乐在人类生活中扮演着至关重要的角色，它是一种有效的治疗方法，可以潜在地减少抑郁、焦虑，改善情绪、自尊和生活质量。音乐具有通过面部表情来改变人类情感的力量。根据情感推荐音乐是一项艰巨的任务。现有的情绪识别和音乐推荐系统侧重于抑郁症和心理健康分析。在此基础上，提出了一种基于面部表情识别的音乐推荐模型，以改善或改变情绪。人脸情感识别(FER)采用YoloV5算法实现。FER的输出是一种分为快乐、愤怒、悲伤和中性的情绪，作为音乐推荐系统的输入。创建音乐播放器是为了根据用户的情绪跟踪用户的最爱。如果用户是系统的新手，那么将会推荐一般化的音乐。本文的目的是根据用户的情感向用户推荐音乐，从而进一步完善音乐。

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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Advances in Computational Intelligence in Materials Science

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