A Study of the Influence of Music on Audiences’ Cognition of Animation

Abstract

How do animation directors and music composers integrate personal creativity and expression into their work, and how do audiences understand and appreciate it as being important and worthy of discussion? This study explores the influence of music on audiences’ cognition of animation by using both quantitative and qualitative methods. Scholars specializing in aesthetics and music have conducted much research on music aesthetics and music itself. In recent years, further studies on music and film have also been carried out. However, there is a lack of research regarding audiences’ cognition of music in animation. This study focuses on the popular form of sand animation and provides insights into audiences’ cognition differences and preferences in order to uncover the core factors. The findings are that: (1) the audience perceived more consistent and subtle differences in the use of musical instruments, rhythm cadence and video–audio fit; there were also obvious differences in the perceptions of vocal skills, performance skills and musical style as well as emotional transmission; (2) three aspects of the audiences’ evaluation of an animation were affected by music: creativity, cultural meaning and preferences. The seven elements that constitute animation music (use of orchestration, vocal skills, musical style, rhythm cadence, performance techniques, emotional transmission and video–audio fit) exerted varying degrees of influence on the audiences’ evaluation of the animation film. Amongst these, video–audio fit was found to be the most important element, as it simultaneously affected the audiences’ evaluation in terms of creativity, cultural meaning and preferences; (3) audiences of different ages and professional backgrounds showed significant differences in evaluating animation films in terms of creativity, culture and preference; and (4) differences in music had a significant impact on audiences’ perceptions and evaluations of 10 facets of animation films, including the story content, role identification and spiritual fit.

A Study on the Relationship between Painter’s Psychology and Anime Creation Style Based on a Deep Neural Network

“…It utilizes unpaired training data and a one-way GAN structure to realize the conversion from realistic to anime scenes. In 2019, Ani Megan was improved based on Cartoon GAN; three loss functions enhance anime vision: grayscale antagonistic loss, grayscale style loss, and color reconstruction loss, which better maintains the color distribution of the original image and generates quality better anime images [ 14 ]. The limitation of these methods is that they can only animate stylized backgrounds such as buildings and landscapes and cannot highly animate abstraction of the five features of a human face [ 15 ].…”