torchaudio.functional.inverse_spectrogram

torchaudio.functional.inverse_spectrogram(spectrogram: Tensor, length: Optional[int], pad: int, window: Tensor, n_fft: int, hop_length: int, win_length: int, normalized: Union[bool, str], center: bool = True, pad_mode: str = 'reflect', onesided: bool = True) → Tensor

Create an inverse spectrogram or a batch of inverse spectrograms from the provided complex-valued spectrogram.

Parameters:

• spectrogram (Tensor) – Complex tensor of audio of dimension (…, freq, time).

• length (int or None) – The output length of the waveform.

• pad (int) – Two sided padding of signal. It is only effective when length is provided.

• window (Tensor) – Window tensor that is applied/multiplied to each frame/window

• n_fft (int) – Size of FFT

• hop_length (int) – Length of hop between STFT windows

• win_length (int) – Window size

• normalized (bool or str) – Whether the stft output was normalized by magnitude. If input is str, choices are "window" and "frame_length", dependent on normalization mode. True maps to "window".

• center (bool, optional) – whether the waveform was padded on both sides so that the \(t\)-th frame is centered at time \(t \times \text{hop\_length}\). Default: True

• pad_mode (string, optional) – controls the padding method used when center is True. This parameter is provided for compatibility with the spectrogram function and is not used. Default: "reflect"

• onesided (bool, optional) – controls whether spectrogram was done in onesided mode. Default: True

Returns:

Dimension (…, time). Least squares estimation of the original signal.

Return type:

Tensor