mindspore.dataset.audio.DeemphBiquad
- class mindspore.dataset.audio.DeemphBiquad(sample_rate)[source]
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: