Music Emotion Research Based on Reinforcement Learning and Multimodal Information. (9th February 2022)
- Record Type:
- Journal Article
- Title:
- Music Emotion Research Based on Reinforcement Learning and Multimodal Information. (9th February 2022)
- Main Title:
- Music Emotion Research Based on Reinforcement Learning and Multimodal Information
- Authors:
- Hu, Yue
- Other Names:
- Jan Naeem Academic Editor.
- Abstract:
- 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.
- Is Part Of:
- Journal of mathematics. Volume 2022(2022)
- Journal:
- Journal of mathematics
- Issue:
- Volume 2022(2022)
- Issue Display:
- Volume 2022, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 2022
- Issue:
- 2022
- Issue Sort Value:
- 2022-2022-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-02-09
- Subjects:
- Mathematics -- Periodicals
Mathematics
Periodicals
510 - Journal URLs:
- https://www.hindawi.com/journals/jmath/ ↗
http://bibpurl.oclc.org/web/74492 ↗
http://search.ebscohost.com/direct.asp?db=a9h&jid=%22FV7F%22&scope=site ↗ - DOI:
- 10.1155/2022/2446399 ↗
- Languages:
- English
- ISSNs:
- 2314-4629
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 21137.xml