| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148 |
- import csv
- import os
- from pathlib import Path
- from typing import Tuple, Union
- import torchaudio
- from torch import Tensor
- from torch.hub import download_url_to_file
- from torch.utils.data import Dataset
- from torchaudio.datasets.utils import extract_archive
- URL = "aew"
- FOLDER_IN_ARCHIVE = "ARCTIC"
- _CHECKSUMS = {
- "http://festvox.org/cmu_arctic/packed/cmu_us_aew_arctic.tar.bz2": "645cb33c0f0b2ce41384fdd8d3db2c3f5fc15c1e688baeb74d2e08cab18ab406", # noqa: E501
- "http://festvox.org/cmu_arctic/packed/cmu_us_ahw_arctic.tar.bz2": "024664adeb892809d646a3efd043625b46b5bfa3e6189b3500b2d0d59dfab06c", # noqa: E501
- "http://festvox.org/cmu_arctic/packed/cmu_us_aup_arctic.tar.bz2": "2c55bc3050caa996758869126ad10cf42e1441212111db034b3a45189c18b6fc", # noqa: E501
- "http://festvox.org/cmu_arctic/packed/cmu_us_awb_arctic.tar.bz2": "d74a950c9739a65f7bfc4dfa6187f2730fa03de5b8eb3f2da97a51b74df64d3c", # noqa: E501
- "http://festvox.org/cmu_arctic/packed/cmu_us_axb_arctic.tar.bz2": "dd65c3d2907d1ee52f86e44f578319159e60f4bf722a9142be01161d84e330ff", # noqa: E501
- "http://festvox.org/cmu_arctic/packed/cmu_us_bdl_arctic.tar.bz2": "26b91aaf48b2799b2956792b4632c2f926cd0542f402b5452d5adecb60942904", # noqa: E501
- "http://festvox.org/cmu_arctic/packed/cmu_us_clb_arctic.tar.bz2": "3f16dc3f3b97955ea22623efb33b444341013fc660677b2e170efdcc959fa7c6", # noqa: E501
- "http://festvox.org/cmu_arctic/packed/cmu_us_eey_arctic.tar.bz2": "8a0ee4e5acbd4b2f61a4fb947c1730ab3adcc9dc50b195981d99391d29928e8a", # noqa: E501
- "http://festvox.org/cmu_arctic/packed/cmu_us_fem_arctic.tar.bz2": "3fcff629412b57233589cdb058f730594a62c4f3a75c20de14afe06621ef45e2", # noqa: E501
- "http://festvox.org/cmu_arctic/packed/cmu_us_gka_arctic.tar.bz2": "dc82e7967cbd5eddbed33074b0699128dbd4482b41711916d58103707e38c67f", # noqa: E501
- "http://festvox.org/cmu_arctic/packed/cmu_us_jmk_arctic.tar.bz2": "3a37c0e1dfc91e734fdbc88b562d9e2ebca621772402cdc693bbc9b09b211d73", # noqa: E501
- "http://festvox.org/cmu_arctic/packed/cmu_us_ksp_arctic.tar.bz2": "8029cafce8296f9bed3022c44ef1e7953332b6bf6943c14b929f468122532717", # noqa: E501
- "http://festvox.org/cmu_arctic/packed/cmu_us_ljm_arctic.tar.bz2": "b23993765cbf2b9e7bbc3c85b6c56eaf292ac81ee4bb887b638a24d104f921a0", # noqa: E501
- "http://festvox.org/cmu_arctic/packed/cmu_us_lnh_arctic.tar.bz2": "4faf34d71aa7112813252fb20c5433e2fdd9a9de55a00701ffcbf05f24a5991a", # noqa: E501
- "http://festvox.org/cmu_arctic/packed/cmu_us_rms_arctic.tar.bz2": "c6dc11235629c58441c071a7ba8a2d067903dfefbaabc4056d87da35b72ecda4", # noqa: E501
- "http://festvox.org/cmu_arctic/packed/cmu_us_rxr_arctic.tar.bz2": "1fa4271c393e5998d200e56c102ff46fcfea169aaa2148ad9e9469616fbfdd9b", # noqa: E501
- "http://festvox.org/cmu_arctic/packed/cmu_us_slp_arctic.tar.bz2": "54345ed55e45c23d419e9a823eef427f1cc93c83a710735ec667d068c916abf1", # noqa: E501
- "http://festvox.org/cmu_arctic/packed/cmu_us_slt_arctic.tar.bz2": "7c173297916acf3cc7fcab2713be4c60b27312316765a90934651d367226b4ea", # noqa: E501
- }
- def load_cmuarctic_item(line: str, path: str, folder_audio: str, ext_audio: str) -> Tuple[Tensor, int, str, str]:
- utterance_id, transcript = line[0].strip().split(" ", 2)[1:]
- # Remove space, double quote, and single parenthesis from transcript
- transcript = transcript[1:-3]
- file_audio = os.path.join(path, folder_audio, utterance_id + ext_audio)
- # Load audio
- waveform, sample_rate = torchaudio.load(file_audio)
- return (waveform, sample_rate, transcript, utterance_id.split("_")[1])
- class CMUARCTIC(Dataset):
- """Create a Dataset for *CMU ARCTIC* [:footcite:`Kominek03cmuarctic`].
- Args:
- 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 download.
- (default: ``"aew"``)
- Allowed type values are ``"aew"``, ``"ahw"``, ``"aup"``, ``"awb"``, ``"axb"``, ``"bdl"``,
- ``"clb"``, ``"eey"``, ``"fem"``, ``"gka"``, ``"jmk"``, ``"ksp"``, ``"ljm"``, ``"lnh"``,
- ``"rms"``, ``"rxr"``, ``"slp"`` or ``"slt"``.
- folder_in_archive (str, optional):
- The top-level directory of the dataset. (default: ``"ARCTIC"``)
- download (bool, optional):
- Whether to download the dataset if it is not found at root path. (default: ``False``).
- """
- _file_text = "txt.done.data"
- _folder_text = "etc"
- _ext_audio = ".wav"
- _folder_audio = "wav"
- def __init__(
- self, root: Union[str, Path], url: str = URL, folder_in_archive: str = FOLDER_IN_ARCHIVE, download: bool = False
- ) -> None:
- if url in [
- "aew",
- "ahw",
- "aup",
- "awb",
- "axb",
- "bdl",
- "clb",
- "eey",
- "fem",
- "gka",
- "jmk",
- "ksp",
- "ljm",
- "lnh",
- "rms",
- "rxr",
- "slp",
- "slt",
- ]:
- url = "cmu_us_" + url + "_arctic"
- ext_archive = ".tar.bz2"
- base_url = "http://www.festvox.org/cmu_arctic/packed/"
- url = os.path.join(base_url, url + ext_archive)
- # Get string representation of 'root' in case Path object is passed
- root = os.fspath(root)
- basename = os.path.basename(url)
- root = os.path.join(root, folder_in_archive)
- if not os.path.isdir(root):
- os.mkdir(root)
- archive = os.path.join(root, basename)
- basename = basename.split(".")[0]
- self._path = os.path.join(root, basename)
- if download:
- if not os.path.isdir(self._path):
- if not os.path.isfile(archive):
- checksum = _CHECKSUMS.get(url, None)
- download_url_to_file(url, archive, hash_prefix=checksum)
- extract_archive(archive)
- else:
- if not os.path.exists(self._path):
- raise RuntimeError(
- f"The path {self._path} doesn't exist. "
- "Please check the ``root`` path or set `download=True` to download it"
- )
- self._text = os.path.join(self._path, self._folder_text, self._file_text)
- with open(self._text, "r") as text:
- walker = csv.reader(text, delimiter="\n")
- self._walker = list(walker)
- def __getitem__(self, n: int) -> Tuple[Tensor, int, str, str]:
- """Load the n-th sample from the dataset.
- Args:
- n (int): The index of the sample to be loaded
- Returns:
- (Tensor, int, str, str): ``(waveform, sample_rate, transcript, utterance_id)``
- """
- line = self._walker[n]
- return load_cmuarctic_item(line, self._path, self._folder_audio, self._ext_audio)
- def __len__(self) -> int:
- return len(self._walker)
|