mindspore.dataset.audio.DeemphBiquad

class mindspore.dataset.audio.DeemphBiquad(sample_rate)

Apply Compact Disc (IEC 60908) de-emphasis (a treble attenuation shelving filter) to the audio waveform.

Similar to SoX implementation.

Parameters

sample_rate (int) – Sampling rate of the waveform, must be 44100 or 48000 (Hz).

Raises

• TypeError – If sample_rate is not of type int.

• ValueError – If sample_rate is not 44100 or 48000.

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

Supported Platforms:

CPU

Examples

>>> import numpy as np
>>> import mindspore.dataset as ds
>>> import mindspore.dataset.audio as audio
>>>
>>> # Use the transform in dataset pipeline mode
>>> waveform = np.random.random([5, 8])  # 5 samples
>>> numpy_slices_dataset = ds.NumpySlicesDataset(data=waveform, column_names=["audio"])
>>> transforms = [audio.DeemphBiquad(44100)]
>>> numpy_slices_dataset = numpy_slices_dataset.map(operations=transforms, input_columns=["audio"])
>>> for item in numpy_slices_dataset.create_dict_iterator(num_epochs=1, output_numpy=True):
...     print(item["audio"].shape, item["audio"].dtype)
...     break
(8,) float64
>>>
>>> # Use the transform in eager mode
>>> waveform = np.random.random([8])  # 1 sample
>>> output = audio.DeemphBiquad(44100)(waveform)
>>> print(output.shape, output.dtype)
(8,) float64

Tutorial Examples:

• Illustration of audio transforms