Research on Machine Semantic Recognition in Different Bel Canto Music Backgrounds

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.