AUTOMATIC DETECTION OF DENSE ORNAMENTATION IN MUSIC

Techniques are disclosed for automatic detection of dense ornamentation in music. Input data representing a piece of digitally encoded music in a time domain is converted into a spectrogram representing time-frequency coefficients in a frequency domain. The spectrogram includes column vectors of the time-frequency coefficients that correspond to time periods spanning different portions of the piece of music. A one-dimensional onset detection array is calculated based on a subset of the column vectors. Using the spectrogram and the onset detection array, a two-dimensional self-similarity matrix (SSM) is calculated based on pair-wise comparisons of elements in the onset detection array. As a result, an irregular pattern score representing the presence of dense ornamentation in the piece of music can be calculated based on a magnitude difference between a beat pattern in the music and each column of the slim SSM.