Research on Multimodal Music Emotion Recognition Method Based on Image Sequence

Zhao Yu,Bai Yuan Ding

doi:10.1155/2021/7087588

Abstract

The work of music performance system is to control the light change by identifying the emotional elements of music. Therefore, once the identification error occurs, it will not be able to create a good stage effect. Therefore, a multimodal music emotion recognition method based on image sequence is studied. The emotional characteristics of music are analyzed, including acoustic characteristics, melody characteristics, and audio characteristics, and the feature vector is constructed. The recognition and classification model based on neural network is trained, the weight and threshold of each layer are adjusted, and then the feature vector is input into the trained model to realize the intelligent recognition and classification of multimodal music emotion. The threshold of the starting point range of a specific humming note is given by the center clipping method, which is used to eliminate the low amplitude part of the humming note signal, extract the short-time spectral structure features and envelope features of the pitch, and complete the multimodal music emotion recognition. The results show that the calculated kappa coefficient k is greater than 0.75, which shows that the recognition and classification results are in good agreement with the actual results, and the classification and recognition accuracy is high.

Highlights

Music is an art form that takes sound as a means of communication and produces emotional experience
E recognition and classification model based on neural network is trained, the weight and threshold of each layer are adjusted, and the feature vector is input into the trained model to realize the intelligent recognition and classification of multimodal music emotion. e threshold of the starting point range of a specific humming note is given by the center clipping method, which is used to eliminate the low amplitude part of the humming note signal, extract the shorttime spectral structure features and envelope features of the pitch, and complete the multimodal music emotion recognition. e recognition and expression of multimodal music emotion enable users to realize emotional humancomputer interaction through music, which enriches the research content of human-computer interaction technology
Based on the results calculated by formula (21), the intelligent recognition of note starting point in feature tone retrieval can be effectively completed, so as to complete the research of multimodal music emotion recognition method based on image sequence

Summary

Introduction

Music is an art form that takes sound as a means of communication and produces emotional experience. With the continuous enrichment of computer music materials, it has become an important research content to use the image sequence intelligent information analysis and processing method to study the emotional information of music works, so as to make the computer have the ability to recognize and express multimodal music emotions like people. In this regard, relevant scholars have proposed many studies. (2) Adjustment formula of connection weight vjt and threshold ct between hidden layer and output layer: Test sample

Result

Intelligent Recognition of Note Starting Point Based on Clipping

Experimental Analysis

GHz 8 GB

Conclusion and Prospect