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Instrumentals/Songs Separation for Background Music Removal

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Information Technology, Systems Research, and Computational Physics (ITSRCP 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 945))

Abstract

The music industry has come a long way since its inception. Music producers have also adhered to modern technology to infuse life into their creations. Systems capable of separating sounds based on sources especially vocals from songs have always been a necessity which has gained attention from researchers as well. The challenge of vocal separation elevates even more in the case of the multi-instrument environment. It is essential for a system to be first able to detect that whether a piece of music contains vocals or not prior to attempting source separation. In this paper, such a system is proposed being tested on a database of more than 99 h of instrumentals and songs. Using line spectral frequency-based features, we have obtained the highest accuracy of 99.78% from among six different classifiers, viz. BayesNet, Support Vector Machine, Multi Layer Perceptron, LibLinear, Simple Logistic and Decision Table.

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Author information

Authors and Affiliations

  1. Department of Computer Science, West Bengal State University, Kolkata, India

    Himadri Mukherjee & Kaushik Roy

  2. Department of Informatics, University of Evora, Évora, Portugal

    Sk Md Obaidullah & Teresa Gonçalves

  3. Department of Computer Science, The University of South Dakota, Vermillion, SD, USA

    K. C. Santosh

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

    Santanu Phadikar

Authors
  1. Himadri Mukherjee
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  2. Sk Md Obaidullah
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  3. K. C. Santosh
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  4. Teresa Gonçalves
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  5. Santanu Phadikar
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  6. Kaushik Roy
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Corresponding author

Correspondence to Himadri Mukherjee .

Editor information

Editors and Affiliations

  1. Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Krakow, Poland

    Piotr Kulczycki

  2. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  3. Faculty of Engineering Sciences, Széchenyi István University, Győr, Hungary

    László T. Kóczy

  4. Faculty of Civil Engineering, Slovak University of Technology, Bratislava, Slovakia

    Radko Mesiar

  5. Department of Electronic Systems, Aalborg University, Aalborg, Denmark

    Rafal Wisniewski

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Mukherjee, H., Obaidullah, S.M., Santosh, K.C., Gonçalves, T., Phadikar, S., Roy, K. (2020). Instrumentals/Songs Separation for Background Music Removal. In: Kulczycki, P., Kacprzyk, J., Kóczy, L., Mesiar, R., Wisniewski, R. (eds) Information Technology, Systems Research, and Computational Physics. ITSRCP 2018. Advances in Intelligent Systems and Computing, vol 945. Springer, Cham. https://doi.org/10.1007/978-3-030-18058-4_19

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