c2acr#

class diffsptk.CepstrumToAutocorrelation(cep_order: int, acr_order: int, n_fft: int = 512)[source]#

See this page for details.

Parameters:

cep_orderint >= 0: The order of the cepstrum, $M$ .
acr_orderint >= 0: The order of the autocorrelation, $N$ .
n_fftint >> N: The number of FFT bins used for conversion. The accurate conversion requires the large value.

forward(c: Tensor) → Tensor[source]#

Convert cepstrum to autocorrelation.

Parameters:

cTensor [shape=(…, M+1)]: The cepstral coefficients.

Returns:

outTensor [shape=(…, N+1)]: The autocorrelation.

Examples

>>> c = diffsptk.nrand(4)
>>> c
tensor([-0.1751,  0.1950, -0.3211,  0.3523, -0.5453])
>>> c2acr = diffsptk.CepstrumToAutocorrelation(4, 4, 16)
>>> r = c2acr(c)
>>> r
tensor([ 1.0672, -0.0485, -0.1564,  0.2666, -0.4551])

diffsptk.functional.c2acr(c: Tensor, acr_order: int, n_fft: int = 512) → Tensor[source]#

Convert cepstrum to autocorrelation.

Parameters:

cTensor [shape=(…, M+1)]: The cepstral coefficients.
acr_orderint >= 0: The order of the autocorrelation, $N$ .
n_fftint >> N: The number of FFT bins used for conversion.

Returns:

outTensor [shape=(…, N+1)]: The autocorrelation.