Musical Genre Classification of Audio Data Using Source Separation Techniques

نویسنده

  • P. S. Lampropoulou
چکیده

We propose a two-step, audio feature-based musical genre classification methodology. First, we identify and separate the various musical instrument sources in the audio signal, using the convolutive sparse coding algorithm. Next, we extract classification features from the separated signals that correspond to distinct musical instrument sources. The methodology is evaluated and its performance is assessed.

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تاریخ انتشار 1994