asteroid.data.dampvsep_dataset module¶
-
class
asteroid.data.dampvsep_dataset.DAMPVSEPSinglesDataset(root_path, task, split='train_singles', ex_per_track=1, random_segments=False, sample_rate=16000, segment=None, norm=None, source_augmentations=None, mixture='original')[source]¶ Bases:
sphinx.ext.autodoc.importer._MockObjectDAMP-VSEP vocal separation dataset
This dataset utilises one of the two preprocessed versions of DAMP-VSEP from https://github.com/groadabike/DAMP-VSEP-Singles aimed for SINGLE SINGER separation.
The DAMP-VSEP dataset is hosted on Zenodo. https://zenodo.org/record/3553059
Parameters: - root_path (str) – Root path to DAMP-VSEP dataset.
- task (str) –
one of
'enh_vocal',``’separation’``.'enh_vocal'for vocal enhanced.'separation'for vocal and background separation.
- split (str) – one of
'train_english','train_singles','valid'and'test'. Default to'train_singles'. - ex_per_track (int, optional) – Number of samples yielded from each track, can be used to increase
dataset size, defaults to
1. - random_segments (boolean, optional) – Enables random offset for track segments.
- sample_rate (int, optional) – Sample rate of files in dataset. Default 16000 Hz
- segment (float, optional) – Duration of segments in seconds,
Defaults to
Nonewhich loads the full-length audio tracks. - norm (Str, optional) –
Type of normalisation to use. Default to
None'song_level'use mixture mean and std.`None`no normalisation
- source_augmentations (Callable, optional) – Augmentations applied to the sources (only).
Default to
None. - mixture (str, optional) –
Whether to use the original mixture with non-linear effects or remix sources. Default to original.
'remix'for use addition to remix the sources.'original'for use the original mixture.
Note
There are 2 train set available:
- train_english: Uses all English spoken song. Duets are converted into 2 singles. Totalling 9243 performances and 77Hrs.
- train_singles: Uses all singles performances, discarding all duets. Totalling 20660 performances and 149 hrs.