Signal Processing - Onset Detection Algorithm

ONSET DETECTION



This is a method which is used to detect the events in sound signals. Specially, the beginning and the ending of a sound signal. 

Proper segmentation of various frequencies of sound and extraction of important features from a particular sound system can be listed as the major uses of this method. 

The signals from different bands are combined in order to get the final signal. In the Drum Device there are signals generated from different bands (Sensing Components). This is known as the multi band separation.

The complexity of the function or the wave generated is reduced and it is transformed into a detected function so that the relevant features of the signal is highlighted and be easily extracted. This is called the signal reduction and it is done based on the features of the signal or may be using parabolistic model.

Once the signal is reduced, the peak picking should be done which describes searching for peaks in detection function.

Prior to apply Onset Detection the signals should be properly smoothed as described above. These preprocessing steps are done in MATLAB and then the onset curve is obtained.

The onset detection should be performed in all three components and their onset locations should be stored in independent vectors.

The same operations must be applied to the sound library which we have created with different sounds of the drum generated when we hit the head of the drum in different styles and the onset curve could be obtained.Then the most suitable sound signal which tally with the final signal obtained from three sensing components can be selected and emitted through the speakers.

This method may not be the most suitable method which can be used to extract and store the signals generate from the sensing components but this would be a good approach to do it.


Reference 01

Reference 02


Author : Pavarindu Sahansith

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