mindspore.dataset.audio.Vad

class mindspore.dataset.audio.Vad(sample_rate, trigger_level=7.0, trigger_time=0.25, search_time=1.0, allowed_gap=0.25, pre_trigger_time=0.0, boot_time=0.35, noise_up_time=0.1, noise_down_time=0.01, noise_reduction_amount=1.35, measure_freq=20.0, measure_duration=None, measure_smooth_time=0.4, hp_filter_freq=50.0, lp_filter_freq=6000.0, hp_lifter_freq=150.0, lp_lifter_freq=2000.0)[source]

Attempt to trim silent background sounds from the end of the voice recording.

Parameters

  • sample_rate (int) – Sample rate of audio signal.

  • trigger_level (float, optional) – The measurement level used to trigger activity detection (default=7.0).

  • trigger_time (float, optional) – The time constant (in seconds) used to help ignore short sounds (default=0.25).

  • search_time (float, optional) – The amount of audio (in seconds) to search for quieter/shorter sounds to include prior to the detected trigger point (default=1.0).

  • allowed_gap (float, optional) – The allowed gap (in seconds) between quiteter/shorter sounds to include prior to the detected trigger point (default=0.25).

  • pre_trigger_time (float, optional) – The amount of audio (in seconds) to preserve before the trigger point and any found quieter/shorter bursts (default=0.0).

  • boot_time (float, optional) – The time for the initial noise estimate (default=0.35).

  • noise_up_time (float, optional) – Time constant used by the adaptive noise estimator, when the noise level is increasing (default=0.1).

  • noise_down_time (float, optional) – Time constant used by the adaptive noise estimator, when the noise level is decreasing (default=0.01).

  • noise_reduction_amount (float, optional) – The amount of noise reduction used in the detection algorithm (default=1.35).

  • measure_freq (float, optional) – The frequency of the algorithm’s processing (default=20.0).

  • measure_duration (float, optional) – The duration of measurement (default=None, use twice the measurement period).

  • measure_smooth_time (float, optional) – The time constant used to smooth spectral measurements (default=0.4).

  • hp_filter_freq (float, optional) – The “Brick-wall” frequency of high-pass filter applied at the input to the detector algorithm (default=50.0).

  • lp_filter_freq (float, optional) – The “Brick-wall” frequency of low-pass filter applied at the input to the detector algorithm (default=6000.0).

  • hp_lifter_freq (float, optional) – The “Brick-wall” frequency of high-pass lifter applied at the input to the detector algorithm (default=150.0).

  • lp_lifter_freq (float, optional) – The “Brick-wall” frequency of low-pass lifter applied at the input to the detector algorithm (default=2000.0).

Examples

>>> import numpy as np
>>>
>>> waveform = np.random.random([2, 1000])
>>> numpy_slices_dataset = ds.NumpySlicesDataset(data=waveform, column_names=["audio"])
>>> transforms = [audio.Vad(sample_rate=600)]
>>> numpy_slices_dataset = numpy_slices_dataset.map(operations=transforms, input_columns=["audio"])