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mindspore.dataset.audio.ComputeDeltas

class mindspore.dataset.audio.ComputeDeltas(win_length=5, pad_mode=BorderType.EDGE)

Compute delta coefficients of a spectrogram.

$$d_t=\frac{\sum _{n=1}^{N}n(c_{t+n}-c_{t-n})}{2\sum _{n=1}^N{n}^2}$$

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"])