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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) | |