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# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. 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.
"""
This script computes features for TTS models prior to training, such as pitch and energy.
The resulting features will be stored in the provided 'feature_dir'.
$ python <nemo_root_path>/scripts/dataset_processing/tts/compute_features.py \
--feature_config_path=<nemo_root_path>/examples/tts/conf/features/feature_22050.yaml \
--manifest_path=<data_root_path>/manifest.json \
--audio_dir=<data_root_path>/audio \
--feature_dir=<data_root_path>/features \
--num_workers=1
"""
import argparse
from pathlib import Path
from hydra.utils import instantiate
from joblib import Parallel, delayed
from omegaconf import OmegaConf
from tqdm import tqdm
from nemo.collections.asr.parts.utils.manifest_utils import read_manifest
def get_args():
parser = argparse.ArgumentParser(
formatter_class=argparse.ArgumentDefaultsHelpFormatter, description="Compute TTS features.",
)
parser.add_argument(
"--feature_config_path", required=True, type=Path, help="Path to feature config file.",
)
parser.add_argument(
"--manifest_path", required=True, type=Path, help="Path to training manifest.",
)
parser.add_argument(
"--audio_dir", required=True, type=Path, help="Path to base directory with audio data.",
)
parser.add_argument(
"--feature_dir", required=True, type=Path, help="Path to directory where feature data will be stored.",
)
parser.add_argument(
"--num_workers", default=1, type=int, help="Number of parallel threads to use. If -1 all CPUs are used."
)
args = parser.parse_args()
return args
def main():
args = get_args()
feature_config_path = args.feature_config_path
manifest_path = args.manifest_path
audio_dir = args.audio_dir
feature_dir = args.feature_dir
num_workers = args.num_workers
if not manifest_path.exists():
raise ValueError(f"Manifest {manifest_path} does not exist.")
if not audio_dir.exists():
raise ValueError(f"Audio directory {audio_dir} does not exist.")
feature_config = OmegaConf.load(feature_config_path)
feature_config = instantiate(feature_config)
featurizers = feature_config.featurizers
entries = read_manifest(manifest_path)
for feature_name, featurizer in featurizers.items():
print(f"Computing: {feature_name}")
Parallel(n_jobs=num_workers)(
delayed(featurizer.save)(manifest_entry=entry, audio_dir=audio_dir, feature_dir=feature_dir,)
for entry in tqdm(entries)
)
if __name__ == "__main__":
main()
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