The index of the buffer where the residual of the sinusoidal component will be reconstructed.
The index of the buffer where the residual of the sinusoidal component will be reconstructed.
ARGUMENT:: bandwidth
ARGUMENT:: bandwidth
The width in bins of the fragment of the fft window that is considered a normal deviation for a potential continuous sinusoidal track. It has an effect on CPU cost: the widest is more accurate but more computationally expensive. It is capped at (fftSize / 2) + 1.
The width in bins of the fragment of the fft window that is considered a normal deviation for a potential continuous sinusoidal track. It has an effect on CPU cost: the widest is more accurate but more computationally expensive. It is capped at (fftSize / 2) + 1.
ARGUMENT:: threshold
ARGUMENT:: detectionThreshold
The normalised threshold, between 0 an 1, to consider a peak as a sinusoidal component from the normalized cross-correlation.
The threshold in dB above which to consider a peak as a sinusoidal component from the normalized cross-correlation.
ARGUMENT:: birthLowThreshold
The threshold in dB above which to consider a peak to start a sinusoidal component tracking, for the low end of the spectrum. It is interpolated across the spectrom until birthHighThreshold at half-Nyquist.
ARGUMENT:: birthHighThreshold
The threshold in dB above which to consider a peak to start a sinusoidal component tracking, for the high end of the spectrum. It is interpolated across the spectrom until birthLowThreshold at DC.
ARGUMENT:: minTrackLen
ARGUMENT:: minTrackLen
The minimum duration, in spectral frames, for a sinusoidal track to be accepted as a partial. It allows to remove space-monkeys, but is more CPU intensive and might reject quick pitch material.
The minimum duration, in spectral frames, for a sinusoidal track to be accepted as a partial. It allows to remove space-monkeys, but is more CPU intensive and might reject quick pitch material.
ARGUMENT:: magWeight
ARGUMENT:: trackingMethod
The weight of the magnitude proximity of a peak when trying to associate it to an existing track (relative to freqWeight - suggested between 0 to 1)
The algorithm used to track the sinusoidal continuity between spectral frames. 0 is the default, "Greedy", and 1 is a more expensive "Munkres". footnote::reference here::
ARGUMENT:: trackMagRange
The frequency difference allowed for a track to diverge between frames, in Hertz.
ARGUMENT:: freqWeight
ARGUMENT:: trackFreqRange
The weight of the frequency proximity of a peak when trying to associate it to an existing track (relative to magWeight - suggested between 0 to 1)
The amplitude difference allowed for a track to diverge between frames, in dB.
ARGUMENT:: windowSize
ARGUMENT:: trackProb
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 probability of the tracking algorithm to find a track. At a value of 0, it will not try outside of the conditions. With a value of 1, it will match 100% of its peaks to a track.
ARGUMENT:: hopSize
ARGUMENT:: hopSize
The window hop size. As sinusoidal estimation relies on spectral frames, we need to move the window forward. It can be any size but low overlap will create audible artefacts. The -1 default value will default to half of windowSize (overlap of 2).
The window hop size. As sinusoidal estimation relies on spectral frames, we need to move the window forward. It can be any size but low overlap will create audible artefacts. The -1 default value will default to half of windowSize (overlap of 2).
The width in bins of the fragment of the fft window that is considered a normal deviation for a potential continuous sinusoidal track. It has an effect on CPU cost: the widest is more accurate but more computationally expensive. It is capped at (fftSize / 2) + 1.
The width in bins of the fragment of the fft window that is considered a normal deviation for a potential continuous sinusoidal track. It has an effect on CPU cost: the widest is more accurate but more computationally expensive. It is capped at (fftSize / 2) + 1.
ARGUMENT:: threshold
ARGUMENT:: detectionThreshold
The normalised threshold, between 0 an 1, to consider a peak as a sinusoidal component from the normalized cross-correlation.
The threshold in dB above which to consider a peak as a sinusoidal component from the normalized cross-correlation.
ARGUMENT:: birthLowThreshold
The threshold in dB above which to consider a peak to start a sinusoidal component tracking, for the low end of the spectrum. It is interpolated across the spectrom until birthHighThreshold at half-Nyquist.
ARGUMENT:: birthHighThreshold
The threshold in dB above which to consider a peak to start a sinusoidal component tracking, for the high end of the spectrum. It is interpolated across the spectrom until birthLowThreshold at DC.
ARGUMENT:: minTrackLen
ARGUMENT:: minTrackLen
The minimum duration, in spectral frames, for a sinusoidal track to be accepted as a partial. It allows to remove space-monkeys, but is more CPU intensive and might reject quick pitch material.
The minimum duration, in spectral frames, for a sinusoidal track to be accepted as a partial. It allows to remove space-monkeys, but is more CPU intensive and might reject quick pitch material.
ARGUMENT:: magWeight
ARGUMENT:: trackingMethod
The weight of the magnitude proximity of a peak when trying to associate it to an existing track (relative to freqWeight - suggested between 0 to 1)
The algorithm used to track the sinusoidal continuity between spectral frames. 0 is the default, "Greedy", and 1 is a more expensive "Munkres". footnote::reference here::
ARGUMENT:: trackMagRange
The frequency difference allowed for a track to diverge between frames, in Hertz.
ARGUMENT:: trackFreqRange
The amplitude difference allowed for a track to diverge between frames, in dB.
ARGUMENT:: freqWeight
ARGUMENT:: trackProb
The weight of the frequency proximity of a peak when trying to associate it to an existing track (relative to magWeight - suggested between 0 to 1)
The probability of the tracking algorithm to find a track. At a value of 0, it will not try outside of the conditions. With a value of 1, it will match 100% of its peaks to a track.
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
Pierre Alexandre Tremblay
6 years ago