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RU. PE. Paiva, T. Mendes, and A. Cardoso, "A Methodology for Detection of Melody in Polyphonic Musical Signals," Paper 6029, (2004 May.). doi: RU. PE. Paiva, T. Mendes, and A. Cardoso, "A Methodology for Detection of Melody in Polyphonic Musical Signals," Paper 6029, (2004 May.). doi:
Abstract: 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.

@article{paiva2004a,
author={paiva, rui pedro and mendes, teresa and cardoso, amilcar},
journal={journal of the audio engineering society},
title={a methodology for detection of melody in polyphonic musical signals},
year={2004},
volume={},
number={},
pages={},
doi={},
month={may},} @article{paiva2004a,
author={paiva, rui pedro and mendes, teresa and cardoso, amilcar},
journal={journal of the audio engineering society},
title={a methodology for detection of melody in polyphonic musical signals},
year={2004},
volume={},
number={},
pages={},
doi={},
month={may},
abstract={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.},}

TY - paper
TI - A Methodology for Detection of Melody in Polyphonic Musical Signals
SP - EP -
AU - Paiva, Rui Pedro
AU - Mendes, Teresa
AU - Cardoso, Amilcar
PY - 2004
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - May 2004 TY - paper
TI - A Methodology for Detection of Melody in Polyphonic Musical Signals
SP - EP -
AU - Paiva, Rui Pedro
AU - Mendes, Teresa
AU - Cardoso, Amilcar
PY - 2004
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - May 2004
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.