Instrumentals/Songs Separation for Background Music Removal

  • Himadri MukherjeeEmail author
  • Sk Md Obaidullah
  • K. C. Santosh
  • Teresa Gonçalves
  • Santanu Phadikar
  • Kaushik Roy
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 945)


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.


Background track Vocals Line spectral frequency Framing 


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Himadri Mukherjee
    • 1
    Email author
  • Sk Md Obaidullah
    • 2
  • K. C. Santosh
    • 3
  • Teresa Gonçalves
    • 2
  • Santanu Phadikar
    • 4
  • Kaushik Roy
    • 1
  1. 1.Department of Computer ScienceWest Bengal State UniversityKolkataIndia
  2. 2.Department of InformaticsUniversity of EvoraÉvoraPortugal
  3. 3.Department of Computer ScienceThe University of South DakotaVermillionUSA
  4. 4.Department of Computer Science and EngineeringMaulana Abul Kalam Azad University of TechnologyKolkataIndia

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