A Methodology for Detection of Melody in Polyphonic Musical Signals

Paiva RP, Mendes T, Cardoso A. A Methodology for Detection of Melody in Polyphonic Musical Signals. In: AES Convention 116. Audio Engineering Society; 2004.pp. 6029:1-. Available from: https://aes.org/publications/elibrary-page/?id=12679

@inproceedings{Paiva2004_12679,
  author = {Paiva, Rui Pedro and Mendes, Teresa and Cardoso, Amilcar},
  title = {{A Methodology for Detection of Melody in Polyphonic Musical Signals}},
  booktitle = {AES Convention 116},
  pages = {6029:1-},
  year = {2004},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=12679}
}

TY  - CPAPER
TI  - A Methodology for Detection of Melody in Polyphonic Musical Signals
AU  - Paiva, Rui Pedro
AU  - Mendes, Teresa
AU  - Cardoso, Amilcar
T2  - AES Convention 116
SP  - 1
M1  - Paper 6029
PY  - 2004
DA  - 2004/05/06
UR  - https://aes.org/publications/elibrary-page/?id=12679
PB  - Audio Engineering Society
LA  - en
AB  - We present a bottom-up method for melody detection in polyphonic musical signals. Our approach is based on the assumption that the melodic line is often salient in terms of note intensity (energy). First, trajectories of the most intense harmonic groups are constructed. Next, note candidates are obtained by trajectory segmentation (in terms of frequency and energy variations). Too short, low-energy and octave-related notes are then eliminated. Finally, the melody is extracted by selecting the most important notes at each time, based on their intensity. We tested our method with excerpts from 12 songs encompassing several genres. In the songs where the solo stands out clearly, most of the melody notes were successfully detected. However, for songs where the melody is not that salient, the algorithm performed poorly. Nevertheless, we could say that the results are encouraging.
ER  -