<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Focusing on virtual chorus, this paper analyzes the training process of VR technology and music choral conductor talents. After the construction of the online data platform, the image splicing, image alignment and image fusion algorithms of VR technology are integrated with the Harris corner detection improvement algorithm to realize the virtual chorus in the context of deep learning. The influence of family support and school aesthetic education on various dimensions of psychological needs for talent cultivation was modeled using structural equation modeling. Based on the data of music teachers using VR technology, mediated effect analysis and total effect analysis were conducted to analyze the factors influencing the use of imagery with VR technology. ANOVA was utilized to compare the data on the four dimensions of rhythmic memory, pitch, melodic memory, and listening ability to verify the effectiveness of VR technology on music teachers’ talent cultivation. The total effect analysis showed that the order of the influence of each influencing factor on the intention to use was 0.361>social influence 0.263>perceived usefulness 0.263>perceived ease of use 0.251>computer self-efficacy 0.169>convenience conditions 0.162>job relevance 0.134>simulation 0.075.</p>
</abstract>

Focusing on virtual chorus, this paper analyzes the training process of VR technology and music choral conductor talents. After the construction of the online data platform, the image splicing, image alignment and image fusion algorithms of VR technology are integrated with the Harris corner detection improvement algorithm to realize the virtual chorus in the context of deep learning. The influence of family support and school aesthetic education on various dimensions of psychological needs for talent cultivation was modeled using structural equation modeling. Based on the data of music teachers using VR technology, mediated effect analysis and total effect analysis were conducted to analyze the factors influencing the use of imagery with VR technology. ANOVA was utilized to compare the data on the four dimensions of rhythmic memory, pitch, melodic memory, and listening ability to verify the effectiveness of VR technology on music teachers’ talent cultivation. The total effect analysis showed that the order of the influence of each influencing factor on the intention to use was 0.361>social influence 0.263>perceived usefulness 0.263>perceived ease of use 0.251>computer self-efficacy 0.169>convenience conditions 0.162>job relevance 0.134>simulation 0.075.

The Value and Realization of Choral Conducting Talent Cultivation for Music Teachers in the Context of Deep Learning

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Focusing on virtual chorus, this paper analyzes the training process of VR technology and music choral conductor talents. After the construction of the online...

The Value and Realization of Choral Conducting Talent Cultivation for Music Teachers in the Context of Deep Learning

Publicado en línea: 16 dic 2023

Páginas: -

Recibido: 14 feb 2023

Aceptado: 26 jun 2023

DOI: https://doi.org/10.2478/amns.2023.2.01492

Palabras clave
VR technology, Image fusion algorithm, Harris corner point detection, Structural equation modeling, Talent development

© 2023 Weiwei Han, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

The Value and Realization of Choral Conducting Talent Cultivation for Music Teachers in the Context of Deep Learning

Publicado en línea: 16 dic 2023

Páginas: -

Recibido: 14 feb 2023

Aceptado: 26 jun 2023

DOI: https://doi.org/10.2478/amns.2023.2.01492

Palabras claveVR technology, Image fusion algorithm, Harris corner point detection, Structural equation modeling, Talent development

© 2023 Weiwei Han, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Palabras clave
VR technology, Image fusion algorithm, Harris corner point detection, Structural equation modeling, Talent development