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import csv
import os
from pathlib import Path
from typing import Dict, List, Tuple, Union
import torchaudio
from torch import Tensor
from torch.utils.data import Dataset
def load_commonvoice_item(
line: List[str], header: List[str], path: str, folder_audio: str, ext_audio: str
) -> Tuple[Tensor, int, Dict[str, str]]:
# Each line as the following data:
# client_id, path, sentence, up_votes, down_votes, age, gender, accent
if header[1] != "path":
raise ValueError(f"expect `header[1]` to be 'path', but got {header[1]}")
fileid = line[1]
filename = os.path.join(path, folder_audio, fileid)
if not filename.endswith(ext_audio):
filename += ext_audio
waveform, sample_rate = torchaudio.load(filename)
dic = dict(zip(header, line))
return waveform, sample_rate, dic
class COMMONVOICE(Dataset):
"""*CommonVoice* :cite:`ardila2020common` dataset.
Args:
root (str or Path): Path to the directory where the dataset is located.
(Where the ``tsv`` file is present.)
tsv (str, optional):
The name of the tsv file used to construct the metadata, such as
``"train.tsv"``, ``"test.tsv"``, ``"dev.tsv"``, ``"invalidated.tsv"``,
``"validated.tsv"`` and ``"other.tsv"``. (default: ``"train.tsv"``)
"""
_ext_txt = ".txt"
_ext_audio = ".mp3"
_folder_audio = "clips"
def __init__(self, root: Union[str, Path], tsv: str = "train.tsv") -> None:
# Get string representation of 'root' in case Path object is passed
self._path = os.fspath(root)
self._tsv = os.path.join(self._path, tsv)
with open(self._tsv, "r") as tsv_:
walker = csv.reader(tsv_, delimiter="\t")
self._header = next(walker)
self._walker = list(walker)
def __getitem__(self, n: int) -> Tuple[Tensor, int, Dict[str, str]]:
"""Load the n-th sample from the dataset.
Args:
n (int): The index of the sample to be loaded
Returns:
Tuple of the following items;
Tensor:
Waveform
int:
Sample rate
Dict[str, str]:
Dictionary containing the following items from the corresponding TSV file;
* ``"client_id"``
* ``"path"``
* ``"sentence"``
* ``"up_votes"``
* ``"down_votes"``
* ``"age"``
* ``"gender"``
* ``"accent"``
"""
line = self._walker[n]
return load_commonvoice_item(line, self._header, self._path, self._folder_audio, self._ext_audio)
def __len__(self) -> int:
return len(self._walker)
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