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| import csv | |
| import os | |
| from pathlib import Path | |
| from typing import Tuple, Union | |
| import torchaudio | |
| from torch import Tensor | |
| from torch.utils.data import Dataset | |
| from torchaudio._internal import download_url_to_file | |
| from torchaudio.datasets.utils import _extract_tar | |
| 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): | |
| """*CMU ARCTIC* :cite:`Kominek03cmuarctic` dataset. | |
| 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_tar(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: | |
| Tuple of the following items; | |
| Tensor: | |
| Waveform | |
| int: | |
| Sample rate | |
| str: | |
| Transcript | |
| str: | |
| 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) | |