Music Segmentation Algorithm Based on Self-Adaptive Update of Confidence Measure

To improve the accuracy of music segmentation and enhance segmentation effect, an algorithm based on the adaptive update of confidence measure is proposed. According to the theory of compressed sensing, the music fragments are denoised, and thus the denoised signals are subjected to short-term corre...

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Autor principal:	Jianhua Li
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/3f6ead73fe2a4ee1b856916ce3585b00
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id	oai:doaj.org-article:3f6ead73fe2a4ee1b856916ce3585b00
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spelling	oai:doaj.org-article:3f6ead73fe2a4ee1b856916ce3585b002021-11-22T01:11:36ZMusic Segmentation Algorithm Based on Self-Adaptive Update of Confidence Measure2314-478510.1155/2021/8329088https://doaj.org/article/3f6ead73fe2a4ee1b856916ce3585b002021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/8329088https://doaj.org/toc/2314-4785To improve the accuracy of music segmentation and enhance segmentation effect, an algorithm based on the adaptive update of confidence measure is proposed. According to the theory of compressed sensing, the music fragments are denoised, and thus the denoised signals are subjected to short-term correlation analysis. Then, the pitch frequency is extracted, and the music fragments are roughly classified by wavelet transform to realize the preprocessing of the music fragments. In order to calculate the confidence measure of the music segment, the SVM method is used, whereas the adaptive update of the confidence measure is studied using reliable data selection algorithm. The dynamic threshold notes are segmented according to the update result to realize music segmentation. Experimental results show that the recall and precision values of the algorithm reach 97.5% and 93.8%, respectively, the segmentation error rate is low, and it can achieve effective segmentation of music fragments, indicating that the algorithm is effective.Jianhua LiHindawi LimitedarticleMathematicsQA1-939ENJournal of Mathematics, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Mathematics QA1-939
spellingShingle	Mathematics QA1-939 Jianhua Li Music Segmentation Algorithm Based on Self-Adaptive Update of Confidence Measure
description	To improve the accuracy of music segmentation and enhance segmentation effect, an algorithm based on the adaptive update of confidence measure is proposed. According to the theory of compressed sensing, the music fragments are denoised, and thus the denoised signals are subjected to short-term correlation analysis. Then, the pitch frequency is extracted, and the music fragments are roughly classified by wavelet transform to realize the preprocessing of the music fragments. In order to calculate the confidence measure of the music segment, the SVM method is used, whereas the adaptive update of the confidence measure is studied using reliable data selection algorithm. The dynamic threshold notes are segmented according to the update result to realize music segmentation. Experimental results show that the recall and precision values of the algorithm reach 97.5% and 93.8%, respectively, the segmentation error rate is low, and it can achieve effective segmentation of music fragments, indicating that the algorithm is effective.
format	article
author	Jianhua Li
author_facet	Jianhua Li
author_sort	Jianhua Li
title	Music Segmentation Algorithm Based on Self-Adaptive Update of Confidence Measure
title_short	Music Segmentation Algorithm Based on Self-Adaptive Update of Confidence Measure
title_full	Music Segmentation Algorithm Based on Self-Adaptive Update of Confidence Measure
title_fullStr	Music Segmentation Algorithm Based on Self-Adaptive Update of Confidence Measure
title_full_unstemmed	Music Segmentation Algorithm Based on Self-Adaptive Update of Confidence Measure
title_sort	music segmentation algorithm based on self-adaptive update of confidence measure
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/3f6ead73fe2a4ee1b856916ce3585b00
work_keys_str_mv	AT jianhuali musicsegmentationalgorithmbasedonselfadaptiveupdateofconfidencemeasure
_version_	1718418276594221056

Music Segmentation Algorithm Based on Self-Adaptive Update of Confidence Measure

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