Novel mathematical model for the classification of music and rhythmic genre using deep neural network
Abstract Music Genre Classification (MGC) is a crucial undertaking that categorizes Music Genre (MG) based on auditory information. MGC is commonly employed in the retrieval of music information. The three main stages of the proposed system are data readiness, feature mining, and categorization. To...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2023-06-01
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| Series: | Journal of Big Data |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40537-023-00789-2 |
| _version_ | 1827916822938124288 |
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| author | Swati A. Patil G. Pradeepini Thirupathi Rao Komati |
| author_facet | Swati A. Patil G. Pradeepini Thirupathi Rao Komati |
| author_sort | Swati A. Patil |
| collection | DOAJ |
| description | Abstract Music Genre Classification (MGC) is a crucial undertaking that categorizes Music Genre (MG) based on auditory information. MGC is commonly employed in the retrieval of music information. The three main stages of the proposed system are data readiness, feature mining, and categorization. To categorize MG, a new neural network was deployed. The proposed system uses features from spectrographs derived from short clips of songs as inputs to a projected scheme building to categorize songs into an appropriate MG. Extensive experiment on the GTZAN dataset, Indian Music Genre(IMG) dataset, Hindustan Music Rhythm (HMR) and Tabala Dataset show that the proposed strategy is more effective than existing methods. Indian rhythms were used to test the proposed system design. The proposed system design was compared with other existing algorithms based on time and space complexity. |
| first_indexed | 2024-03-13T03:20:46Z |
| format | Article |
| id | doaj.art-008b957ff9dc409885da95a26037f58b |
| institution | Directory Open Access Journal |
| issn | 2196-1115 |
| language | English |
| last_indexed | 2024-03-13T03:20:46Z |
| publishDate | 2023-06-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Big Data |
| spelling | doaj.art-008b957ff9dc409885da95a26037f58b2023-06-25T11:19:39ZengSpringerOpenJournal of Big Data2196-11152023-06-0110111710.1186/s40537-023-00789-2Novel mathematical model for the classification of music and rhythmic genre using deep neural networkSwati A. Patil0G. Pradeepini1Thirupathi Rao Komati2Department of Computer Science and Engineering, Koneru Lakshmaiah Education FoundationDepartment of Computer Science and Engineering, Koneru Lakshmaiah Education FoundationGST GITAM Deemed to be UniversityAbstract Music Genre Classification (MGC) is a crucial undertaking that categorizes Music Genre (MG) based on auditory information. MGC is commonly employed in the retrieval of music information. The three main stages of the proposed system are data readiness, feature mining, and categorization. To categorize MG, a new neural network was deployed. The proposed system uses features from spectrographs derived from short clips of songs as inputs to a projected scheme building to categorize songs into an appropriate MG. Extensive experiment on the GTZAN dataset, Indian Music Genre(IMG) dataset, Hindustan Music Rhythm (HMR) and Tabala Dataset show that the proposed strategy is more effective than existing methods. Indian rhythms were used to test the proposed system design. The proposed system design was compared with other existing algorithms based on time and space complexity.https://doi.org/10.1186/s40537-023-00789-2Mathematical modelNeural networkFeature extractionMGTime complexitySpace complexity |
| spellingShingle | Swati A. Patil G. Pradeepini Thirupathi Rao Komati Novel mathematical model for the classification of music and rhythmic genre using deep neural network Journal of Big Data Mathematical model Neural network Feature extraction MG Time complexity Space complexity |
| title | Novel mathematical model for the classification of music and rhythmic genre using deep neural network |
| title_full | Novel mathematical model for the classification of music and rhythmic genre using deep neural network |
| title_fullStr | Novel mathematical model for the classification of music and rhythmic genre using deep neural network |
| title_full_unstemmed | Novel mathematical model for the classification of music and rhythmic genre using deep neural network |
| title_short | Novel mathematical model for the classification of music and rhythmic genre using deep neural network |
| title_sort | novel mathematical model for the classification of music and rhythmic genre using deep neural network |
| topic | Mathematical model Neural network Feature extraction MG Time complexity Space complexity |
| url | https://doi.org/10.1186/s40537-023-00789-2 |
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