torchaudio.functional.filtfilt

torchaudio.functional.filtfilt(waveform: Tensor, a_coeffs: Tensor, b_coeffs: Tensor, clamp: bool = True) → Tensor

Apply an IIR filter forward and backward to a waveform.

Inspired by https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.filtfilt.html

Parameters:

• waveform (Tensor) – audio waveform of dimension of (…, time). Must be normalized to -1 to 1.

• a_coeffs (Tensor) – denominator coefficients of difference equation of dimension of either 1D with shape (num_order + 1) or 2D with shape (num_filters, num_order + 1). Lower delay coefficients are first, e.g. [a0, a1, a2, ...]. Must be same size as b_coeffs (pad with 0’s as necessary).

• b_coeffs (Tensor) – numerator coefficients of difference equation of dimension of either 1D with shape (num_order + 1) or 2D with shape (num_filters, num_order + 1). Lower delay coefficients are first, e.g. [b0, b1, b2, ...]. Must be same size as a_coeffs (pad with 0’s as necessary).

• clamp (bool, optional) – If True, clamp the output signal to be in the range [-1, 1] (Default: True)

Returns:

Waveform with dimension of either (…, num_filters, time) if a_coeffs and b_coeffs are 2D Tensors, or (…, time) otherwise.

Return type:

Tensor