The size of a smoothing filter that is applied on the novelty curve. A larger filter filter size allows for cleaner cuts on very sharp changes.
The size of a smoothing filter that is applied on the novelty curve. A larger filter filter size allows for cleaner cuts on very sharp changes.
ARGUMENT:: minSliceLength
The minimum duration of a slice in number of hopSize.
ARGUMENT:: windowSize
ARGUMENT:: windowSize
The window size. As novelty estimation relies on spectral frames, we need to decide what precision we give it spectrally and temporally, in line with Gabor Uncertainty principles. http://www.subsurfwiki.org/wiki/Gabor_uncertainty
The window size. As novelty estimation relies on spectral frames, we need to decide what precision we give it spectrally and temporally, in line with Gabor Uncertainty principles. http://www.subsurfwiki.org/wiki/Gabor_uncertainty
@ -167,5 +170,5 @@ Routine{
)
)
// list the indicies of detected attacks - the two input channels have been summed
// list the indicies of detected attacks - the two input channels have been summed
The size of a smoothing filter that is applied on the novelty curve. A larger filter filter size allows for cleaner cuts on very sharp changes.
The size of a smoothing filter that is applied on the novelty curve. A larger filter filter size allows for cleaner cuts on very sharp changes.
ARGUMENT:: minSliceLength
The minimum duration of a slice in number of hopSize.
ARGUMENT:: windowSize
ARGUMENT:: windowSize
The window size. As sinusoidal estimation relies on spectral frames, we need to decide what precision we give it spectrally and temporally, in line with Gabor Uncertainty principles. http://www.subsurfwiki.org/wiki/Gabor_uncertainty
The window size. As sinusoidal estimation relies on spectral frames, we need to decide what precision we give it spectrally and temporally, in line with Gabor Uncertainty principles. http://www.subsurfwiki.org/wiki/Gabor_uncertainty
@ -53,8 +56,7 @@ ARGUMENT:: maxFilterSize
This cannot be modulated.
This cannot be modulated.
RETURNS::
RETURNS::
An audio stream with impulses at detected transients. The latency between the input and the output is (windowSize +
An audio stream with impulses at detected transients. The latency between the input and the output is STRONG::hopSize * (((kernelSize+1)/2) + filterSize):: at minimum.