def BUILD_ARGPARSE():
parser = argparse.ArgumentParser(description='Processes and Downloads Freesound dataset')
parser = add_data_opts(parser)
parser.add_argument("--target-dir", default='Freesound_dataset/', type=str, help="Directory to store the dataset.")
parser.add_argument("--filter_human_sounds", default='Freesound_dataset/', type=str,
help="Directory to store the dataset.")
args = parser.parse_args()
return args
import os
import wget
import tarfile
import argparse
import subprocess
from deepspeech_pytorch.data.data_opts import add_data_opts
from tqdm import tqdm
import shutil
from deepspeech_pytorch.data.utils import create_manifest
parser = argparse.ArgumentParser(
description='Processes and downloads LibriSpeech dataset.')
parser = add_data_opts(parser)
parser.add_argument("--target-dir",
default='LibriSpeech_dataset/',
type=str,
help="Directory to store the dataset.")
parser.add_argument('--files-to-use',
default="train-clean-100.tar.gz,"
"train-clean-360.tar.gz,train-other-500.tar.gz,"
"dev-clean.tar.gz,dev-other.tar.gz,"
"test-clean.tar.gz,test-other.tar.gz",
type=str,
help='list of file names to download')
args = parser.parse_args()
LIBRI_SPEECH_URLS = {
"train": [
"http://www.openslr.org/resources/12/train-clean-100.tar.gz",
