mindspore.dataset.audio.RiaaBiquad
- class mindspore.dataset.audio.RiaaBiquad(sample_rate)[source]
Apply RIAA vinyl playback equalization.
Similar to SoX implementation.
- Parameters
sample_rate (int) – sampling rate of the waveform, e.g. 44100 (Hz), can only be one of 44100, 48000, 88200, 96000.
- Raises
TypeError – If sample_rate is not of type int.
ValueError – If sample_rate is not any of [44100, 48000, 88200, 96000].
- 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, 24]) # 5 samples >>> numpy_slices_dataset = ds.NumpySlicesDataset(data=waveform, column_names=["audio"]) >>> transforms = [audio.RiaaBiquad(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 (24,) float64 >>> >>> # Use the transform in eager mode >>> waveform = np.random.random([24]) # 1 sample >>> output = audio.RiaaBiquad(44100)(waveform) >>> print(output.shape, output.dtype) (24,) float64
- Tutorial Examples: