{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T11:03:35Z","timestamp":1776078215700,"version":"3.50.1"},"reference-count":16,"publisher":"Wiley","license":[{"start":{"date-parts":[[2021,11,12]],"date-time":"2021-11-12T00:00:00Z","timestamp":1636675200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Scientific Programming"],"published-print":{"date-parts":[[2021,11,12]]},"abstract":"<jats:p>The music performance system works by identifying the emotional elements of music to control the lighting changes. However, if there is a recognition error, a good stage effect will not be able to create. Therefore, this paper proposes an intelligent music emotion recognition and classification algorithm in the music performance system. The first part of the algorithm is to analyze the emotional features of music, including acoustic features, melody features, and audio features. Then, the three kinds of features are combined together to form a feature vector set. In the latter part of the algorithm, it divides the feature vector set into training samples and test samples. The training samples are trained by using recognition and classification model based on the neural network. And then, the testing samples are input into the trained model, which is aiming to realize the intelligent recognition and classification of music emotion. The result shows that the kappa coefficient k values calculated by the proposed algorithm are greater than 0.75, which indicates that the recognition and classification results are consistent with the actual results, and the accuracy of recognition and classification is high. So, the research purpose is achieved.<\/jats:p>","DOI":"10.1155\/2021\/7886570","type":"journal-article","created":{"date-parts":[[2021,11,12]],"date-time":"2021-11-12T23:35:46Z","timestamp":1636760146000},"page":"1-9","source":"Crossref","is-referenced-by-count":5,"title":["Research on Music Emotion Intelligent Recognition and Classification Algorithm in Music Performance System"],"prefix":"10.1155","volume":"2021","author":[{"given":"Chun","family":"Huang","sequence":"first","affiliation":[{"name":"General Education and International College, Chongqing College of Electronic Engineering, ChongQing 400031, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1356-3059","authenticated-orcid":true,"given":"Diao","family":"Shen","sequence":"additional","affiliation":[{"name":"General Education and International College, Chongqing College of Electronic Engineering, ChongQing 400031, China"}]}],"member":"311","reference":[{"issue":"11","key":"1","first-page":"95","article-title":"Research on stage lighting control method based on music emotion recognition","volume":"28","author":"Z. Duan","year":"2020","journal-title":"Computer Measurement and Control"},{"issue":"07","key":"2","first-page":"100","article-title":"Speech emotion recognition algorithm on extraction of deep space attention characteristics based on spectrogram","volume":"35","author":"J. Wang","year":"2019","journal-title":"Telecommunication Science"},{"issue":"8","key":"3","first-page":"24","article-title":"Classification of musical emotions oriented to Chinese lyrics","author":"J. Wang","year":"2019","journal-title":"Computer Systems & Applications"},{"issue":"2","key":"4","first-page":"528","article-title":"Sentiment classification of music features based on PNN","volume":"40","author":"L. Qiang","year":"2019","journal-title":"Computer Engineering and Design"},{"issue":"3","key":"5","first-page":"801","article-title":"Classifying emotional EEG using sparse representation method","volume":"36","author":"X. Deng","year":"2019","journal-title":"Application Research of Computers"},{"issue":"1","key":"6","first-page":"70","article-title":"Multi-feature speech emotion recognition based on random forest classification optimization","volume":"36","author":"G. Li","year":"2019","journal-title":"Microellectronics & Computer"},{"issue":"21","key":"7","first-page":"51","article-title":"Research on classification of electronic music signals based on particle swarm optimization and support vector machine","volume":"43","author":"C. E. Li","year":"2020","journal-title":"Modern electronic technology"},{"issue":"3","key":"8","first-page":"330","article-title":"Research on long term music emotion based on dynamic brain network","volume":"59","author":"H. Li","year":"2020","journal-title":"Journal of Fudan University ( Natural Science)"},{"issue":"2","key":"9","first-page":"61","article-title":"UGC automatic emotion recognition method based on joint optimization of feature selection and dispositional analysis","volume":"33","author":"X. Li","year":"2019","journal-title":"Journal of Industrial Engineering and Engineering Management"},{"issue":"2","key":"10","first-page":"219","article-title":"Passive sonar target classification and recognition technique based on BPSO-KNN algorithm","volume":"38","author":"Z. Zhu","year":"2019","journal-title":"Acoustic technology"},{"issue":"5","key":"11","first-page":"166","article-title":"Design of music emotion classification method based on audio and lyrics dual mode","volume":"39","author":"N. Lu","year":"2020","journal-title":"Techniques of Automation and Applications"},{"issue":"19","key":"12","first-page":"49","article-title":"Design of intelligent detection algorithm for electronic music signal in complex noise scene","volume":"43","author":"X. Jing","year":"2020","journal-title":"Modern electronic technology"},{"issue":"9","key":"13","first-page":"117","article-title":"Electronic music classification model based on multi feature fusion and machine learning algorithm","volume":"36","author":"L. Yi","year":"2020","journal-title":"Microcomputer Applications"},{"issue":"6","key":"14","first-page":"82","article-title":"Research on speech emotion recognition algorithm based on ensemble learning","volume":"30","author":"T. Li","year":"2020","journal-title":"Computer Technology and Development"},{"issue":"7","key":"15","first-page":"1133","article-title":"Speech emotion recognition algorithm based on multi task learning and recurrent neural network","volume":"35","author":"T. Feng","year":"2019","journal-title":"Signal Processing"},{"issue":"2","key":"16","first-page":"344","article-title":"Speech emotion recognition based on BP neural network optimized by improved genetic algorithm","volume":"36","author":"C. Chuang","year":"2019","journal-title":"Application Research of Computers"}],"container-title":["Scientific Programming"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/sp\/2021\/7886570.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/sp\/2021\/7886570.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/sp\/2021\/7886570.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,11,12]],"date-time":"2021-11-12T23:35:46Z","timestamp":1636760146000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/sp\/2021\/7886570\/"}},"subtitle":[],"editor":[{"given":"Bai Yuan","family":"Ding","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2021,11,12]]},"references-count":16,"alternative-id":["7886570","7886570"],"URL":"https:\/\/doi.org\/10.1155\/2021\/7886570","relation":{},"ISSN":["1875-919X","1058-9244"],"issn-type":[{"value":"1875-919X","type":"electronic"},{"value":"1058-9244","type":"print"}],"subject":[],"published":{"date-parts":[[2021,11,12]]}}}