+ General Information
+ Members
+ Research
+ Intranet



15th workshop gRFIA

9th Music Encoding Conference (MEI 2021)


Alicante, July 19-23

13th international workshop on Machine Learning and Music


(online) September 18, 2020



  1. Pertusa A., Iñesta, J.M.
    "Polyphonic monotimbral music transcription using dynamic networks"
    Pattern Recognition Letters, vol. 26, pp. 1809-1818 (2005)
    : bibtex : pdf

    The automatic extraction of the notes that were played in a digital musical signal (automatic music transcription) is an open problem. A number of techniques have been applied to solve it without concluding results. The monotimbral polyphonic version of the problem is posed here: a single instrument has been played and more than one note can sound at the same time. This work tries to approach it through the identification of the pattern of a given instrument in the frequency domain. This is achieved using time-delay neural networks that are fed with the band-grouped spectrogram of a polyphonic monotimbral music recording. The use of a learning scheme based on examples like neural networks permits our system to avoid the use of an auditory model to approach this problem. A number of issues have to be faced to have a robust and powerful system, but promising results using synthesized instruments are presented.

@article {
 author = "Pertusa A., Iñesta, J.M.",
 title  = "Polyphonic monotimbral music transcription using dynamic networks",
 issn = "0167-8655",
 journal = "Pattern Recognition Letters",
 month = "september",
 number = "12",
 pages = "1809-1818",
 volume = "26",
 year = "2005"
Valid XHTML 1.0!Valid CSS!