mindspore.dataset.audio.transforms.AllpassBiquad

class mindspore.dataset.audio.transforms.AllpassBiquad(sample_rate, central_freq, Q=0.707)[source]

Design two-pole all-pass filter with central frequency and bandwidth for audio waveform.

An all-pass filter changes the audio’s frequency to phase relationship without changing its frequency to amplitude relationship. The system function is:

\[H(s) = \frac{s^2 - \frac{s}{Q} + 1}{s^2 + \frac{s}{Q} + 1}\]

Similar to SoX implementation.

Note

The dimension of the audio waveform to be processed needs to be (…, time).

Parameters

  • sample_rate (int) – Sampling rate (in Hz), which can’t be zero.

  • central_freq (float) – Central frequency (in Hz).

  • Q (float, optional) – Quality factor , in range of (0, 1]. Default: 0.707.

Raises

  • TypeError – If sample_rate is not of type integer.

  • ValueError – If sample_rate is 0.

  • TypeError – If central_freq is not of type float.

  • TypeError – If Q is not of type float.

  • ValueError – If Q is not in range of (0, 1].

  • RuntimeError – If input tensor is not in shape of <…, time>.

Supported Platforms:

CPU

Examples

>>> import numpy as np
>>>
>>> waveform = np.array([[2.716064453125e-03, 6.34765625e-03], [9.246826171875e-03, 1.0894775390625e-02]])
>>> numpy_slices_dataset = ds.NumpySlicesDataset(data=waveform, column_names=["audio"])
>>> transforms = [audio.AllpassBiquad(44100, 200.0)]
>>> numpy_slices_dataset = numpy_slices_dataset.map(operations=transforms, input_columns=["audio"])