mindspore.dataset.audio.SpectralCentroid

class mindspore.dataset.audio.SpectralCentroid(sample_rate, n_fft=400, win_length=None, hop_length=None, pad=0, window=WindowType.HANN)[source]

Create a spectral centroid from an audio signal.

Parameters

  • sample_rate (int) – Sampling rate of the waveform, e.g. 44100 (Hz).

  • n_fft (int, optional) – Size of FFT, creates n_fft // 2 + 1 bins (default=400).

  • win_length (int, optional) – Window size (default=None, will use n_fft).

  • hop_length (int, optional) – Length of hop between STFT windows (default=None, will use win_length // 2).

  • pad (int, optional) – Two sided padding of signal (default=0).

  • window (WindowType, optional) – Window function that is applied/multiplied to each frame/window, which can be WindowType.BARTLETT, WindowType.BLACKMAN, WindowType.HAMMING, WindowType.HANN or WindowType.KAISER (default=WindowType.HANN).

Examples

>>> import numpy as np
>>>
>>> waveform = np.random.random([5, 10, 20])
>>> numpy_slices_dataset = ds.NumpySlicesDataset(data=waveform, column_names=["audio"])
>>> transforms = [audio.SpectralCentroid(44100)]
>>> numpy_slices_dataset = numpy_slices_dataset.map(operations=transforms, input_columns=["audio"])