pyACA.FeatureSpectralKurtosis Namespace Reference

Functions
	FeatureSpectralKurtosis (X, f_s)
	computes the spectral kurtosis from the magnitude spectrum

Function Documentation

FeatureSpectralKurtosis()

FeatureSpectralKurtosis	(		X,
			f_s )

computes the spectral kurtosis from the magnitude spectrum

Parameters

X	spectrogram (dimension FFTLength X Observations)
f_s	sample rate of audio data

Returns

vsk: spectral kurtosis

Definition at line 14 of file FeatureSpectralKurtosis.py.

def FeatureSpectralKurtosis(X, f_s):
 
    isSpectrum = X.ndim == 1
    if isSpectrum:
        X = np.expand_dims(X, axis=1)
 
    k = np.arange(0, X.shape[0]) 
    # get spectral centroid and spread (mean and std of dist)
    vsc = FeatureSpectralCentroid(X, f_s)  * 2 / f_s * (X.shape[0]-1)
    vss = FeatureSpectralSpread(X, f_s)    * 2 / f_s * (X.shape[0]-1)
 
    norm = X.sum(axis=0)
    norm[norm == 0] = 1
    vss[vss == 0] = 1
 
    # compute kurtosis
    vsk = np.zeros(X.shape[1])
    for n in range(0, X.shape[1]):
        vsk[n] = np.dot((k - vsc[n])**4, X[:, n]) / (vss[n]**4 * norm[n])
 
    return np.squeeze(vsk - 3) if isSpectrum else (vsk - 3)