Research on Machine Semantic Recognition in Different Bel Canto Music Backgrounds. (12th July 2022)
- Record Type:
- Journal Article
- Title:
- Research on Machine Semantic Recognition in Different Bel Canto Music Backgrounds. (12th July 2022)
- Main Title:
- Research on Machine Semantic Recognition in Different Bel Canto Music Backgrounds
- Authors:
- Ke, Feng
- Other Names:
- Li Qiangyi Academic Editor.
- Abstract:
- Abstract : In order to improve the intelligent analysis effect of Bel Canto music and improve the singing skills of Bel Canto, this paper uses the machine semantic recognition algorithm to identify the characteristics of Bel Canto music, builds a Bel Canto music feature recognition model, and analyzes the advantages and disadvantages of each Bel Canto semantic feature clustering method and the applicable data set types. Finally, this paper applies the Bel Canto semantic feature clustering method to multicomponent signal parameter estimation, uses the clustering method to cluster the time-frequency analysis of nonstationary signals, obtains the time-frequency distribution of each signal component, and then estimates the parameters of each single-component signal. The experimental results show that the Bel Canto music feature recognition method based on machine semantics proposed in this paper has a good effect.
- Is Part Of:
- Advances in multimedia. Volume 2022(2022)
- Journal:
- Advances in multimedia
- 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:
- 2022-07-12
- Subjects:
- Multimedia systems -- Periodicals
Computer networks -- Periodicals
Multimédia
Réseaux d'ordinateurs
Computer networks
Multimedia systems
Periodicals
006.7 - Journal URLs:
- https://www.hindawi.com/journals/am/ ↗
http://bibpurl.oclc.org/web/22854 ↗ - DOI:
- 10.1155/2022/9509672 ↗
- Languages:
- English
- ISSNs:
- 1687-5680
- 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:
- 22701.xml