pyACA.PitchSpectralAcf Namespace Reference

Functions
	PitchSpectralAcf (X, f_s)
	computes f0 via the maximum of the spectral autocorrelation function

Function Documentation

PitchSpectralAcf()

PitchSpectralAcf	(		X,
			f_s )

computes f0 via the maximum of the spectral autocorrelation function

Parameters

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

Returns

f_0: fundamental frequency (in Hz)

Definition at line 13 of file PitchSpectralAcf.py.

def PitchSpectralAcf(X, f_s):
 
    # initialize
    f_min = 300
    f_0 = np.zeros(X.shape[1])
 
    # use spectral symmetry for robustness
    X[0, :] = np.max(X)
    X = np.concatenate((np.flipud(X[1:,:]), X[:-1,:]), axis=0)
 
    # compute the ACF
    for n in range(0, X.shape[1]):
 
        if X[:, n].sum() < 1e-20:
            continue
 
        eta_min = int(round(f_min / f_s * (X.shape[0] - 2))) - 1
 
        afCorr = np.correlate(X[:, n], X[:, n], "full") / np.dot(X[:, n], X[:, n])
        afCorr = afCorr[np.arange(X.shape[0], afCorr.size)]
 
        # find the highest local maximum
        iPeaks = find_peaks(afCorr, height=0)
        if iPeaks[0].size:
            eta_min = np.max([eta_min, iPeaks[0][0] - 1])
        f_0[n] = np.argmax(afCorr[np.arange(eta_min, afCorr.size)]) + 1
 
        # find max index and convert to Hz (note: X has double length)
        f_0[n] = (f_0[n] + eta_min) / (X.shape[0] - 2) * f_s
 
    return f_0