istft#

diffsptk.ISTFT#: alias of InverseShortTimeFourierTransform

class diffsptk.InverseShortTimeFourierTransform(frame_length, frame_period, fft_length, *, center=True, window='blackman', norm='power')[source]#

This is the opposite module to ShortTimeFourierTransform().

Parameters:

frame_lengthint >= 1: The frame length in samples, \(L\).
frame_periodint >= 1: The frame period in samples, \(P\).
fft_lengthint >= L: The number of FFT bins, \(N\).
centerbool: If True, pad the input on both sides so that the frame is centered.
window[‘blackman’, ‘hamming’, ‘hanning’, ‘bartlett’, ‘trapezoidal’, ‘rectangular’, ‘nuttall’]: The window type.
norm[‘none’, ‘power’, ‘magnitude’]: The normalization type of the window.

forward(y, out_length=None)[source]#

Compute inverse short-time Fourier transform.

Parameters:

yTensor [shape=(…, T/P, N/2+1)]: The complex spectrogram.
out_lengthint > 0 or None: The length of the output waveform.

Returns:

outTensor [shape=(…, T)]: The reconstructed waveform.

Examples

>>> x = diffsptk.ramp(1, 3)
>>> x
tensor([1., 2., 3.])
>>> stft_params = {"frame_length": 3, "frame_period": 1, "fft_length": 8}
>>> stft = diffsptk.STFT(**stft_params, out_format="complex")
>>> istft = diffsptk.ISTFT(**stft_params)
>>> y = istft(stft(x), out_length=3)
>>> y
tensor([1., 2., 3.])

diffsptk.functional.istft(y, *, out_length=None, frame_length=400, frame_period=80, fft_length=512, center=True, window='blackman', norm='power')[source]#

Compute inverse short-time Fourier transform.

Parameters:

yTensor [shape=(…, T/P, N/2+1)]: The complex spectrogram.
out_lengthint >= 1 or None: The length of the output waveform.
frame_lengthint >= 1: The frame length in samples, \(L\).
frame_periodint >= 1: The frame period in samples, \(P\).
fft_lengthint >= L: The number of FFT bins, \(N\).
centerbool: If True, pad the input on both sides so that the frame is centered.
window[‘blackman’, ‘hamming’, ‘hanning’, ‘bartlett’, ‘trapezoidal’, ‘rectangular’, ‘nuttall’]: The window type.
norm[‘none’, ‘power’, ‘magnitude’]: The normalization type of the window.

Returns:

outTensor [shape=(…, T)]: The reconstructed waveform.

istft#

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