istft¶
- paddle.signal. istft ( x, n_fft, hop_length=None, win_length=None, window=None, center=True, normalized=False, onesided=True, length=None, return_complex=False, name=None ) [source]
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Inverse short-time Fourier transform (ISTFT).
- Reconstruct time-domain signal from the giving complex input and window tensor when
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nonzero overlap-add (NOLA) condition is met:
\[\sum_{t = -\infty}^{\infty}% ext{window}^2[n - t imes H]\\]eq 0, ext{for } all n
Where: - \(t\): The \(t\)-th input window. - \(N\): Value of n_fft. - \(H\): Value of hop_length.
- Result of istft expected to be the inverse of paddle.signal.stft, but it is
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not guaranteed to reconstruct a exactly realizible time-domain signal from a STFT complex tensor which has been modified (via masking or otherwise). Therefore, istft gives the [Griffin-Lim optimal estimate](https://ieeexplore.ieee.org/document/1164317) (optimal in a least-squares sense) for the corresponding signal.
- Args:
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- x (Tensor): The input data which is a 2-dimensional or 3-dimensional complesx
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Tensor with shape […, n_fft, num_frames].
n_fft (int): The size of Fourier transform. hop_length (int, optional): Number of steps to advance between adjacent windows
from time-domain signal and 0 < hop_length < win_length. Default: None`( treated as equal to `n_fft//4)
- win_length (int, optional): The size of window. Default: `None`(treated as equal
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to n_fft)
- window (Tensor, optional): A 1-dimensional tensor of size win_length. It will
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be center padded to length n_fft if win_length < n_fft. It should be a real-valued tensor if return_complex is False. Default: None`(treated as a rectangle window with value equal to 1 of size `win_length).
- center (bool, optional): It means that whether the time-domain signal has been
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center padded. Default: True.
- normalized (bool, optional): Control whether to scale the output by 1/sqrt(n_fft).
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Default: False
- onesided (bool, optional): It means that whether the input STFT tensor is a half
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of the conjugate symmetry STFT tensor transformed from a real-valued signal and istft will return a real-valued tensor when it is set to True. Default: True.
- length (int, optional): Specify the length of time-domain signal. Default: `None`(
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treated as the whole length of signal).
- return_complex (bool, optional): It means that whether the time-domain signal is
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real-valued. If return_complex is set to True, onesided should be set to False cause the output is complex.
- name (str, optional): The default value is None. Normally there is no need for user
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to set this property. For more information, please refer to Name.
- Returns:
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- A tensor of least squares estimation of the reconstructed signal(s) with shape
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[…, seq_length]
- Examples:
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import numpy as np import paddle from paddle.signal import stft, istft paddle.seed(0) # STFT x = paddle.randn([8, 48000], dtype=paddle.float64) y = stft(x, n_fft=512) # [8, 257, 376] # ISTFT x_ = istft(y, n_fft=512) # [8, 48000] np.allclose(x, x_) # True