spec#
- class diffsptk.Spectrum(fft_length, *, eps=0, relative_floor=None, out_format='power')[source]#
See this page for details.
- Parameters:
- fft_lengthint >= 2
Number of FFT bins, \(L\).
- epsfloat >= 0
A small value added to power spectrum.
- relative_floorfloat < 0 or None
Relative floor in decibels.
- out_format[‘db’, ‘log-magnitude’, ‘magnitude’, ‘power’]
Output format.
- forward(b=None, a=None)[source]#
Compute spectrum.
- Parameters:
- bTensor [shape=(…, M+1)] or None
Framed waveform or numerator coefficients.
- aTensor [shape=(…, N+1)] or None
Denominator coefficients.
- Returns:
- outTensor [shape=(…, L/2+1)]
Spectrum.
Examples
>>> x = diffsptk.ramp(1, 3) >>> x tensor([1., 2., 3.]) >>> spec = diffsptk.Spectrum(8) >>> y = spec(x) >>> y tensor([36.0000, 25.3137, 8.0000, 2.6863, 4.0000])
- diffsptk.functional.spec(b=None, a=None, *, fft_length=512, eps=0, relative_floor=None, out_format='power')[source]#
Compute spectrum.
- Parameters:
- bTensor [shape=(…, M+1)] or None
Numerator coefficients.
- aTensor [shape=(…, N+1)] or None
Denominator coefficients.
- fft_lengthint >= 2
Number of FFT bins, \(L\).
- epsfloat >= 0
A small value added to power spectrum.
- relative_floorfloat < 0 or None
Relative floor in decibels.
- out_format[‘db’, ‘log-magnitude’, ‘magnitude’, ‘power’]
Output format.
- Returns:
- outTensor [shape=(…, L/2+1)]
Spectrum.
See also