mindspore.dataset.audio.AllpassBiquad
- class mindspore.dataset.audio.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 shape 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 int.
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 >>> import mindspore.dataset as ds >>> >>> 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 = [ds.audio.AllpassBiquad(44100, 200.0)] >>> numpy_slices_dataset = numpy_slices_dataset.map(operations=transforms, input_columns=["audio"])
- Tutorial Examples: