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Taxonomy of Music Genre Using Machine Intelligence from Feature Melting Technique

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Intelligent Human Centered Computing (Human 2023)

Part of the book series: Springer Tracts in Human-Centered Computing ((STHCC))

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Abstract

Music is an effectual therapy in our life that makes us calm, cheerful, and excited. Music genre classification (MGC) is essential for recommendation of music and information retrieval. In our proposed work, an effective automatic musical genre classification approach has been experimented with where different features and order are fused together to get a better progressive result than the existing method. Frame-wise extraction of time-domain features(Wavelet scattering, Zero Crossing Rate, energy) and frequency-domain features(Mel Frequency Cepstral Coefficient-MFCC, pitch, Linear Predictive Coefficient-LPC) is done here. After that, the mean value of each extracted feature is put in a vector and fed to the classifier. Two well-known machine learning (ML) algorithms, Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) are used to classify the GTZAN dataset. The proposed method outperformed than the existing work.

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Authors and Affiliations

  1. Department of Computer Science, Vidyasagar University, Midnapore, West Bengal, 721102, India

    Debashri Das Adhikary, Tanushree Dey, Somnath Bera, Sumita Guchhhait, Utpal Nandi & Bachchu Paul

  2. Begum Rokeya University, Park Mor, Modern, 5404, Rangpur, Bangladesh

    Mehadi Hasan

Authors
  1. Debashri Das Adhikary
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  2. Tanushree Dey
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  3. Somnath Bera
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  4. Sumita Guchhhait
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  5. Utpal Nandi
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  6. Mehadi Hasan
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  7. Bachchu Paul
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Corresponding author

Correspondence to Bachchu Paul .

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Editors and Affiliations

  1. Algebra University College, Zagreb, Croatia

    Siddhartha Bhattacharyya

  2. Department of Computer Science and Engineering (AI & ML), Bengal Institute of Technology, Kolkata, India

    Jyoti Sekhar Banerjee

  3. Department of Computer Science and Engineering, Maulana Abul Kalam Azad University of Technology, Kolkata, West Bengal, India

    Debashis De

  4. Department of Computer Science, Nottingham Trent University, Nottingham, UK

    Mufti Mahmud

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Das Adhikary, D. et al. (2023). Taxonomy of Music Genre Using Machine Intelligence from Feature Melting Technique. In: Bhattacharyya, S., Banerjee, J.S., De, D., Mahmud, M. (eds) Intelligent Human Centered Computing. Human 2023. Springer Tracts in Human-Centered Computing. Springer, Singapore. https://doi.org/10.1007/978-981-99-3478-2_3

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