asteroid.data.whamr_dataset module

class asteroid.data.whamr_dataset.WhamRDataset(json_dir, task, sample_rate=8000, segment=4.0, nondefault_nsrc=None)

Bases: sphinx.ext.autodoc.importer._MockObject

Dataset class for WHAMR source separation and speech enhancement tasks.

Parameters:

• json_dir (str) – The path to the directory containing the json files.
• task (str) –

  One of 'sep_clean', 'sep_noisy', 'sep_reverb' or 'sep_reverb_noisy'.

  • 'sep_clean' for two-speaker clean (anechoic) source separation.
  • 'sep_noisy' for two-speaker noisy (anechoic) source separation.
  • 'sep_reverb' for two-speaker clean reverberant source separation.
  • 'sep_reverb_noisy' for two-speaker noisy reverberant source separation.
• sample_rate (int, optional) – The sampling rate of the wav files.
• segment (float, optional) – Length of the segments used for training, in seconds. If None, use full utterances (e.g. for test).
• nondefault_nsrc (int, optional) – Number of sources in the training targets. If None, defaults to one for enhancement tasks and two for separation tasks.

References

“WHAMR!: Noisy and Reverberant Single-Channel Speech Separation”, Maciejewski et al. 2020

dataset_name = 'WHAMR'

__getitem__(idx)

Gets a mixture/sources pair. :returns: mixture, vstack([source_arrays])

get_infos()

Get dataset infos (for publishing models).

Returns:dict, dataset infos with keys dataset, task and licences.