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Abstract
Music is a carrier of emotions, capable of triggering, expressing, and conveying people's innermost emotional experiences. With the development of digital technology, the recognition of emotions in music has been the subject of extensive research. From the viewpoint of application, MER is of great significance in music personalized recommendation services, psychotherapy, music creation, and music visualization. Currently, MER implementation methods based on machine learning are gradually becoming mainstream. This study starts from the basic knowledge of MER, first introduces the relevant research directions and research background of MER, and then proposes a three-part research framework combining MER and MEC. Based on this research framework, the machine learning algorithms and specific applications involved in the framework are introduced. Finally, the challenges and future paths facing the implementation of MER technology are proposed. Provide a reference for improving the accuracy and quality of using artificial intelligence methods to capture music characteristics and expressiveness.
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