Automatic detection of dense ornamentation in music

摘要

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.

主权项

1. A method of detecting dense ornamentation in digital music, the method comprising:
receiving, by a computer processor, input data representing a piece of digitally encoded music in a time domain; converting, by the computer processor, the input data into a spectrogram representing a two-dimensional matrix of time-frequency coefficients in a frequency domain, the spectrogram including a plurality of column vectors of the time-frequency coefficients that correspond to a plurality of time periods spanning different portions of the piece of music; calculating, by the computer processor, a one-dimensional onset detection array based on at least one of the column vectors in the spectrogram; generating, by the computer processor, data representing a two-dimensional self-similarity matrix based on pair-wise comparisons of elements in the onset detection array; applying, by the computer processor, a median filter to the self-similarity matrix to produce data representing a beat pattern for the piece of digital music; calculating, by the computer processor, an irregular pattern score based on a difference between the beat pattern data and the self-similarity matrix data, wherein the irregular pattern score represents a presence of dense ornamentation in the piece of music; and causing, by the computer processor, a change in a multimedia playback based on the calculated irregular pattern score.