mindspore.dataset.audio.ComputeDeltas
- class mindspore.dataset.audio.ComputeDeltas(win_length=5, pad_mode=BorderType.EDGE)[source]
Compute delta coefficients of a spectrogram.
\[d_{t}=\frac{{\textstyle\sum_{n=1}^{N}}n(c_{t+n}-c_{t-n})}{2{\textstyle\sum_{n=1}^{N}}n^{2}}\]- Parameters
win_length (int, optional) – The window length used for computing delta, must be no less than 3 (default=5).
pad_mode (BorderType, optional) –
Mode parameter passed to padding (default=BorderType.EDGE).It can be any of [BorderType.CONSTANT, BorderType.EDGE, BorderType.REFLECT, BordBorderTypeer.SYMMETRIC].
BorderType.CONSTANT, means it fills the border with constant values.
BorderType.EDGE, means it pads with the last value on the edge.
BorderType.REFLECT, means it reflects the values on the edge omitting the last value of edge.
BorderType.SYMMETRIC, means it reflects the values on the edge repeating the last value of edge.
Examples
>>> import numpy as np >>> from mindspore.dataset.audio import BorderType >>> >>> waveform = np.random.random([1, 400 // 2 + 1, 30]) >>> numpy_slices_dataset = ds.NumpySlicesDataset(data=waveform, column_names=["audio"]) >>> transforms = [audio.ComputeDeltas(win_length=7, pad_mode=BorderType.EDGE)] >>> numpy_slices_dataset = numpy_slices_dataset.map(operations=transforms, input_columns=["audio"])