Scientists and researchers have tried to establish a bond between the emotions conveyed and the subsequent mood perceived in a person. Emotions play a major role in terms of our choices, preferences, and decision-making. Emotions appear whenever a person perceives a change in their surroundings or within their body. Since early times, a considerable amount of effort has been made in the field of emotion detection and mood estimation. Listening to music forms a major part of our daily life. The music we listen to, the emotions it induces, and the resulting mood are all interrelated in ways we are unbeknownst to, and our survey is entirely based on these two areas of research. Differing viewpoints on this issue have led to the proposal of different ways of emotion annotation, model training, and result visualization. This paper provides a detailed review of the methods proposed in music mood recognition. It also discusses the different sensors that have been utilized to acquire various physiological signals. This paper will focus upon the datasets created and reused, different classifiers employed to obtain results with higher accuracy, features extracted from the acquired signals, and music along with an attempt to determine the exact features and parameters that will help in improving the classification process. It will also investigate several techniques to detect emotions and the different music models used to assess the music mood. This review intends to answer the questions and research issues in identifying human emotions and music mood to provide a greater insight into this field of interest and develop a better understanding to comprehend and answer the perplexing problems that surround us.

科学家和研究人员试图在所传达的情绪和随后的人的情绪之间建立联系。情绪在我们的选择，偏好和决策方面起着重要作用。每当一个人感知到周围环境或身体内部的变化时，就会出现情绪。自早期以来，在情绪检测和情绪估计领域已经做出了相当大的努力。听音乐是我们日常生活的重要组成部分。我们所听的音乐，所引起的情感以及由此产生的心情都以我们不为人所知的方式相互关联，我们的调查完全基于这两个研究领域。关于这个问题的不同观点导致提出了不同的情感注释，模型训练和结果可视化方法。本文详细介绍了在音乐情绪识别中提出的方法。它还讨论了已用于获取各种生理信号的不同传感器。本文将重点介绍创建和重用的数据集，用于获得更高准确性的结果的不同分类器，从所采集信号中提取的特征以及音乐，以及尝试确定有助于改善分类过程的确切特征和参数。它还将研究几种检测情绪的技术以及用于评估音乐情绪的不同音乐模型。