asteroid.data.kinect_wsj module

asteroid.data.kinect_wsj.make_dataloaders(train_dir, valid_dir, n_src=2, sample_rate=16000, segment=4.0, batch_size=4, num_workers=None, **kwargs)

class asteroid.data.kinect_wsj.KinectWsjMixDataset(json_dir, n_src=2, sample_rate=16000, segment=4.0)

Bases: asteroid.data.wsj0_mix.Wsj0mixDataset

Dataset class for the KinectWSJ-mix source separation dataset.

Parameters:

• json_dir (str) – The path to the directory containing the json files.
• 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).
• n_src (int, optional) – Number of sources in the training targets.

References

“Analyzing the impact of speaker localization errors on speech separation for automatic speech recognition”, Sunit Sivasankaran et al. 2020.

dataset_name = 'Kinect-WSJ'

__getitem__(idx)

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

mixture is of dimension [samples, channels] sources are of dimension [n_src, samples, channels]

get_infos()

Get dataset infos (for publishing models).

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