LIBRISPEECH

class torchaudio.datasets.LIBRISPEECH(root: Union[str, Path], url: str = 'train-clean-100', folder_in_archive: str = 'LibriSpeech', download: bool = False)

LibriSpeech [Panayotov et al., 2015] dataset.

Parameters:

• root (str or Path) – Path to the directory where the dataset is found or downloaded.

• url (str, optional) – The URL to download the dataset from, or the type of the dataset to dowload. Allowed type values are "dev-clean", "dev-other", "test-clean", "test-other", "train-clean-100", "train-clean-360" and "train-other-500". (default: "train-clean-100")

• folder_in_archive (str, optional) – The top-level directory of the dataset. (default: "LibriSpeech")

• download (bool, optional) – Whether to download the dataset if it is not found at root path. (default: False).

__getitem__

LIBRISPEECH.__getitem__(n: int) → Tuple[Tensor, int, str, int, int, int]

Load the n-th sample from the dataset.

Parameters:

n (int) – The index of the sample to be loaded

Returns:

Tuple of the following items;

Tensor:

Waveform

int:

Sample rate

str:

Transcript

int:

Speaker ID

int:

Chapter ID

int:

Utterance ID

get_metadata

LIBRISPEECH.get_metadata(n: int) → Tuple[Tensor, int, str, int, int, int]

Get metadata for the n-th sample from the dataset. Returns filepath instead of waveform, but otherwise returns the same fields as __getitem__().

Parameters:

n (int) – The index of the sample to be loaded

Returns:

Tuple of the following items;

str:

Path to audio

int:

Sample rate

str:

Transcript

int:

Speaker ID

int:

Chapter ID

int:

Utterance ID