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import logging
import os
from typing import Optional
from TTS.utils.download import download_kaggle_dataset, download_url, extract_archive
logger = logging.getLogger(__name__)
def download_ljspeech(path: str):
"""Download and extract LJSpeech dataset
Args:
path (str): path to the directory where the dataset will be stored.
"""
os.makedirs(path, exist_ok=True)
url = "https://data.keithito.com/data/speech/LJSpeech-1.1.tar.bz2"
download_url(url, path)
basename = os.path.basename(url)
archive = os.path.join(path, basename)
extract_archive(archive)
def download_vctk(path: str, use_kaggle: Optional[bool] = False):
"""Download and extract VCTK dataset.
Args:
path (str): path to the directory where the dataset will be stored.
use_kaggle (bool, optional): Downloads vctk dataset from kaggle. Is generally faster. Defaults to False.
"""
if use_kaggle:
download_kaggle_dataset("mfekadu/english-multispeaker-corpus-for-voice-cloning", "VCTK", path)
else:
os.makedirs(path, exist_ok=True)
url = "https://datashare.ed.ac.uk/bitstream/handle/10283/3443/VCTK-Corpus-0.92.zip"
download_url(url, path)
basename = os.path.basename(url)
archive = os.path.join(path, basename)
extract_archive(archive)
def download_tweb(path: str):
"""Download and extract Tweb dataset
Args:
path (str): Path to the directory where the dataset will be stored.
"""
download_kaggle_dataset("bryanpark/the-world-english-bible-speech-dataset", "TWEB", path)
def download_libri_tts(path: str, subset: Optional[str] = "all"):
"""Download and extract libri tts dataset.
Args:
path (str): Path to the directory where the dataset will be stored.
subset (str, optional): Name of the subset to download. If you only want to download a certain
portion specify it here. Defaults to 'all'.
"""
subset_dict = {
"libri-tts-clean-100": "http://www.openslr.org/resources/60/train-clean-100.tar.gz",
"libri-tts-clean-360": "http://www.openslr.org/resources/60/train-clean-360.tar.gz",
"libri-tts-other-500": "http://www.openslr.org/resources/60/train-other-500.tar.gz",
"libri-tts-dev-clean": "http://www.openslr.org/resources/60/dev-clean.tar.gz",
"libri-tts-dev-other": "http://www.openslr.org/resources/60/dev-other.tar.gz",
"libri-tts-test-clean": "http://www.openslr.org/resources/60/test-clean.tar.gz",
"libri-tts-test-other": "http://www.openslr.org/resources/60/test-other.tar.gz",
}
os.makedirs(path, exist_ok=True)
if subset == "all":
for sub, val in subset_dict.items():
logger.info("Downloading %s...", sub)
download_url(val, path)
basename = os.path.basename(val)
archive = os.path.join(path, basename)
extract_archive(archive)
logger.info("All subsets downloaded")
else:
url = subset_dict[subset]
download_url(url, path)
basename = os.path.basename(url)
archive = os.path.join(path, basename)
extract_archive(archive)
def download_thorsten_de(path: str):
"""Download and extract Thorsten german male voice dataset.
Args:
path (str): Path to the directory where the dataset will be stored.
"""
os.makedirs(path, exist_ok=True)
url = "https://www.openslr.org/resources/95/thorsten-de_v02.tgz"
download_url(url, path)
basename = os.path.basename(url)
archive = os.path.join(path, basename)
extract_archive(archive)
def download_mailabs(path: str, language: str = "english"):
"""Download and extract Mailabs dataset.
Args:
path (str): Path to the directory where the dataset will be stored.
language (str): Language subset to download. Defaults to english.
"""
language_dict = {
"english": "https://data.solak.de/data/Training/stt_tts/en_US.tgz",
"german": "https://data.solak.de/data/Training/stt_tts/de_DE.tgz",
"french": "https://data.solak.de/data/Training/stt_tts/fr_FR.tgz",
"italian": "https://data.solak.de/data/Training/stt_tts/it_IT.tgz",
"spanish": "https://data.solak.de/data/Training/stt_tts/es_ES.tgz",
}
os.makedirs(path, exist_ok=True)
url = language_dict[language]
download_url(url, path)
basename = os.path.basename(url)
archive = os.path.join(path, basename)
extract_archive(archive)
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