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Circuits, Systems, and Signal Processing

, Volume 37, Issue 7, pp 2911–2933 | Cite as

Predominant Melody Extraction from Vocal Polyphonic Music Signal by Time-Domain Adaptive Filtering-Based Method

  • M. Gurunath Reddy
  • K. Sreenivasa Rao
Article
  • 126 Downloads

Abstract

In this paper, a time-domain adaptive filtering-based melody extraction method is proposed. The proposed method works in multiple stages to extract the vocal melody (singer’s fundamental frequency) from vocal polyphonic music signals. The vocal and non-vocal regions of the music signal are identified by the strength of excitation of the source signal. The vocal regions are further segmented into the sequence of notes by detecting their onsets in the frequency representation of the composite signal. The melody contour in each of the vocal note segment is obtained by adaptive zero-frequency filtering in the time domain. The performance of the proposed melody extraction method is compared with the current state-of-the-art melody extraction method in respect of voicing recall rate, voicing false alarm rate, raw pitch, and overall accuracy.

Keywords

Polyphonic Vocals Music signal Melody Zero-frequency filter Onsets Strength of excitation Note boundaries Melody contour 

Notes

Acknowledgements

The present work is carried out under the project entitled “Scientific Approach to Networking and Designing of Heritage Interfaces (SANDHI)” sponsored by Ministry of Human Resource Development (MHRD), Govt. of India. Project reference IIT/SRIC/R/ITA/2014/40, dated March 24, 2014. We would like to thank Google (Google PhD Fellowship) and Department of Information Technology (DIT), Govt. of India for financial support. We would also like to thank Prof. Pallab Das Gupta (Dept. of Computer Science and Engineering, IIT Kharagpur), Prof. Priyadarshi Patnaik (Dept. of Humanities, IIT Kharagpur), and Ms. Gowri (Professional Hindustani music vocalist) for providing us the more theoretical insight into the Hindustani Music.

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.Indian Institute of Technology KharagpurKharagpurIndia

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