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artcraft/models/tts/NeMo/scripts/dataset_processing/process_degli_data.py
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Python

# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import argparse
import sys
from nemo.collections.tts.data.datalayers import preprocess_linear_specs_dataset
sys.path.insert(0, '../')
def main():
parser = argparse.ArgumentParser(
description='Create dataset fitted for training and validating deep griffin iteration from wavefiles'
)
parser.add_argument(
"-v",
"--valid_filelist",
help="Filelist for validation set, with all validation audio files listed",
required=True,
default=None,
type=str,
)
parser.add_argument(
"-t",
"--train_filelist",
help="Filelist for train set, with all train audio files listed",
required=True,
default=None,
type=str,
)
parser.add_argument(
"-n",
"--n_fft",
help="Value for the n_fft parameter, and the filter length for the STFT",
default=512,
type=int,
)
parser.add_argument("--hop_length", help="STFT parameter", default=256, type=int)
parser.add_argument(
"-d", "--destination", help="Destination to save the preprocessed data set to", default="/tmp", type=str
)
parser.add_argument(
"-s",
"--num_snr",
help="Number of distinctive noisy samples to generate for each clear sample at the file list",
default=1,
type=int,
)
args = parser.parse_args()
preprocess_linear_specs_dataset(
args.valid_filelist, args.train_filelist, args.n_fft, args.hop_length, args.num_snr, args.destination
)
if __name__ == "__main__":
main()