Music Emotion Research Based on Reinforcement Learning and Multimodal Information

Yue Hu and Naeem Jan

Journal of Mathematics, 2022, vol. 2022, 1-9

Abstract: Music is an important carrier of emotion and an indispensable factor in people’s daily life. With the rapid growth of digital music, people’s demand for music emotion analysis and retrieval is also increasing. With the rapid development of Internet technology, digital music has been derived continuously, and automatic recognition of music emotion has become the main research focus. For music, emotion is the most essential feature and the deepest inner feeling. Under the ubiquitous information environment, revealing the deep semantic information of multimodal information resources and providing users with integrated information services has important research and application value. In this paper, a multimodal fusion algorithm for music emotion analysis is proposed, and a dynamic model based on reinforcement learning is constructed to improve the analysis accuracy. The model dynamically adjusts the emotional analysis results by learning the user’s behavior, so as to realize the personalized customization of the user’s emotional preference.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/jmath/2022/2446399.pdf (application/pdf)
http://downloads.hindawi.com/journals/jmath/2022/2446399.xml (application/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jjmath:2446399

DOI: 10.1155/2022/2446399

Access Statistics for this article

More articles in Journal of Mathematics from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().