fftcep#
- class diffsptk.CepstralAnalysis(cep_order, fft_length, n_iter=0, accel=0)[source]#
See this page for details.
- Parameters:
- cep_orderint >= 0
Order of cepstrum,
.- fft_lengthint >= 2M
Number of FFT bins,
.- n_iterint >= 0
Number of iterations.
- accelfloat >= 0
Acceleration factor.
References
[1]S. Imai et al., “Spectral envelope extraction by improved cepstral method,” IEICE trans, vol. J62-A, no. 4, pp. 217-223, 1979 (in Japanese).
- forward(x)[source]#
Estimate cepstrum from spectrum.
- Parameters:
- xTensor [shape=(…, L/2+1)]
Power spectrum.
- Returns:
- outTensor [shape=(…, M+1)]
Cepstrum.
Examples
>>> x = diffsptk.ramp(19) >>> stft = diffsptk.STFT(frame_length=10, frame_period=10, fft_length=16) >>> fftcep = diffsptk.CepstralAnalysis(3, 16) >>> c = fftcep(stft(x)) >>> c tensor([[-0.9663, 0.8190, -0.0932, -0.0152], [-0.8539, 4.6173, -0.5496, -0.3207]])
- diffsptk.functional.fftcep(x, cep_order, n_iter=0, accel=0)[source]#
Estimate cepstrum from spectrum.
- Parameters:
- xTensor [shape=(…, L/2+1)]
Power spectrum.
- cep_orderint >= 0
Order of cepstrum,
.- n_iterint >= 0
Number of iterations.
- accelfloat >= 0
Acceleration factor.
- Returns:
- outTensor [shape=(…, M+1)]
Cepstrum.