Leonidas Ioannidis

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by automatic makam description Leonidas Ioannidis Music Technology Group, Universitat Pompeu Fabra Iwannidis_8@yahoo.gr Emilia Music Technology Group, Universitat Pompeu Fabra emilia.gomez@upf.edu Perfecto Herrera Music Technology Group, Universitat Pompeu Fabra perfecto.herrera@upf.edu Abstract The automatic description of music from traditions that do(More)
In this paper we propose a method for singing voice detection in popular music recordings. The method is based on statistical learning of spectral features extracted from the audio tracks. In our method we use Mel Frequency Cepstrum Coefficients (MFCC) to train two Gaussian Mixture Models (GMM). Special attention is brought to our novel approach for(More)
This paper describes our work on automatic classification of phonation modes on singing voice. In the first part of the paper, we will briefly review the main characteristics of the different phonation modes. Then, we will describe the isolated vowels databases we used, with emphasis on a new database we recorded specifically for the purpose of this work.(More)
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