[grfia]
+ General Information
+ Members
+ Research
+ Intranet

PRAIg '16 / +pics

[]



AERFAI Summer School on Deep Learning

[]

Alicante July 5-6, 2017

10th international workshop on Machine Learning and Music

[]

Barcelona: 16th October 2017

Publications:

All

  1. Rizo D., Ponce de León P.J., Pertusa A., Pérez-Sancho C., Iñesta J.M.
    "Melody track identification in music symbolic files"
    Proc. of the 19th Int. FLAIRS Conference, ISBN: 978-1-57735-261-7 (2006)
    : bibtex : pdf
    Abstract:

    The objective of this work is to find the melodic line in MIDI files. Usually, the melodic line is stored in a single track, while the other tracks contain the accompaniment. The detection of the track that contains the melodic line can be very useful for a number of applications, such as melody matching when searching in MIDI databases. The system was developed using WEKA. First, a set of descriptors from each track of the target melody is extracted. These descriptors are the input to a random forest classifier that assigns a probability of being a melodic line to each track. The tracks with a probability under a given threhold are filtered out, and the one with the highest probability is selected as the melodic line of that melody. Promising results were obtained testing different MIDI databases.

@inproceedings {
 author = "Rizo D., Ponce de León P.J., Pertusa A., Pérez-Sancho C., Iñesta J.M.",
 title  = "Melody track identification in music symbolic files",
 booktitle = "Proc. of the 19th Int. FLAIRS Conference",
 isbn = "978-1-57735-261-7",
 publisher = "AAAI Press",
 year = "2006"
}
Valid XHTML 1.0!Valid CSS!