The use of deep learning algorithm and digital media art in all-media intelligent electronic music system

Abstract

In the development of digital media art, to explore the preliminary application of deep learning method in intelligent electronic music system, and promote the integration of deep learning method and digital media technology, thus providing a direction for the development of all media intelligent system, based on deep deterministic policy gradient (DDPG), to solve the multi-task problem in intelligent system, a multi-task learning-based DDPG algorithm (M-DDPG) is proposed. Furthermore, a DDPG algorithm based on hierarchical learning (H-DDPG) is proposed for the hierarchical analysis of images in intelligent system. Aiming at the problem of image classification in intelligent system, through the setting of simulation environment, the application effect of several algorithms in intelligent electronic music system is evaluated. The results show that: M-DDPG algorithm can more accurately complete the operation of related tasks, the reward received by the intelligent system is more than 0.35, and the test results based on eight tasks are more accurate and effective. Even in the case of task error, the algorithm still shows good training results. H-DDPG algorithm has good effect for complex task processing. The accuracy rate of task test corresponding to intelligent system in different scenarios is above 95%, which is better than other conventional algorithms in task test; the self-reinforcement network algorithm can promote the improvement of image classification effect. Several algorithms proposed show excellent performance in image processing of intelligent system, and have great application potential.

Music Recognition and Classification Algorithm considering Audio Emotion

“…e propagation of the neural network includes forward propagation and back-propagation [29]; forward propagation refers to the propagation of the model from the bottom up, calculated based on a given input value; back-propagation calculates losses based on forward propagation calculations and then calculates and trains each neuron parameter using a gradient descent algorithm [30].…”

Optimization of Digital Media Art Creation Process Based on Dual Transformer Residual Network (DTRN) and Lotus Effect Optimization Algorithm (LEA)

“…Visual communication encompasses the use of visual elements, such as animated GIFs, images, movies, diagrams, canvases, and slide deck presentations to communicate concepts or information [2]. Digital media education encompasses digital color art education as well, and knowledge of the state of digital media art research today offers insights examination of the state of digital color art education at the moment [3]. Additionally, educational technology programs have begun incorporating audiovisual art as a fundamental course [4].…”

Design of intelligent evaluation algorithm for music word and song matching based on neural network

“…Therefore, this paper tries to give an accurate and objective intelligent evaluation by comprehensively considering the emotion of lyrics and the rhythm relationship between lyrics, expounds the intelligent evaluation algorithm of music lyrics matching degree based on NN, collects the historical behavior information of music users, and constructs the user preference model by using the method of matrix decomposition of hidden semantic model; Then, the audio resources in the system are preprocessed, and the Mel spectrogram which can represent the music characteristics is extracted. Then, the NN is trained to obtain the regression model for the prediction of the potential characteristics of music, and the users and music are projected into a shared hidden space [4][5] . Finally, TopN recommendation is generated for the target user by calculating the similarity between the user's preference characteristics and the potential characteristics of music.…”