acorr#

class diffsptk.Autocorrelation(frame_length, acr_order, norm=False, estimator='none')[source]#

See this page for details.

Parameters:

frame_lengthint > M: Frame length, \(L\).
acr_orderint >= 0: Order of autocorrelation, \(M\).
normbool: If True, normalize the autocorrelation.
estimator[‘none’, ‘biased’, ‘unbiased’]: Estimator of autocorrelation.

forward(x)[source]#

Estimate autocorrelation of input.

Parameters:

xTensor [shape=(…, L)]: Framed waveform.

Returns:

outTensor [shape=(…, M+1)]: Autocorrelation.

Examples

>>> x = diffsptk.ramp(4)
>>> acorr = diffsptk.Autocorrelation(5, 3)
>>> r = acorr(x)
>>> r
tensor([30.0000, 20.0000, 11.0000,  4.0000])

diffsptk.functional.acorr(x, acr_order, norm=False, estimator='none')[source]#

Compute autocorrelation.

Parameters:

xTensor [shape=(…, L)]: Framed waveform.
acr_orderint >= 0: Order of autocorrelation, \(M\).
normbool: If True, normalize the autocorrelation.
estimator[‘none’, ‘biased’, ‘unbiased’]: Estimator of autocorrelation.

Returns:

outTensor [shape=(…, M+1)]: Autocorrelation.

See also

frame levdur lpc