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PaddleSpeech/parakeet/exps/voice_cloning/tacotron2_ge2e/extract_mel.py

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3.3 KiB

# Copyright (c) 2021 PaddlePaddle Authors. 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 multiprocessing as mp
from functools import partial
from pathlib import Path
import numpy as np
import tqdm
from parakeet.audio import AudioProcessor
from parakeet.audio.spec_normalizer import LogMagnitude
from parakeet.audio.spec_normalizer import NormalizerBase
from parakeet.exps.voice_cloning.tacotron2_ge2e.config import get_cfg_defaults
def extract_mel(fname: Path,
input_dir: Path,
output_dir: Path,
p: AudioProcessor,
n: NormalizerBase):
relative_path = fname.relative_to(input_dir)
out_path = (output_dir / relative_path).with_suffix(".npy")
out_path.parent.mkdir(parents=True, exist_ok=True)
wav = p.read_wav(fname)
mel = p.mel_spectrogram(wav)
mel = n.transform(mel)
np.save(out_path, mel)
def extract_mel_multispeaker(config, input_dir, output_dir, extension=".wav"):
input_dir = Path(input_dir).expanduser()
fnames = list(input_dir.rglob(f"*{extension}"))
output_dir = Path(output_dir).expanduser()
output_dir.mkdir(parents=True, exist_ok=True)
p = AudioProcessor(config.sample_rate, config.n_fft, config.win_length,
config.hop_length, config.d_mels, config.fmin,
config.fmax)
n = LogMagnitude(1e-5)
func = partial(
extract_mel, input_dir=input_dir, output_dir=output_dir, p=p, n=n)
with mp.Pool(16) as pool:
list(
tqdm.tqdm(
pool.imap(func, fnames), total=len(fnames), unit="utterance"))
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description="Extract mel spectrogram from processed wav in AiShell3 training dataset."
)
parser.add_argument(
"--config",
type=str,
help="yaml config file to overwrite the default config")
parser.add_argument(
"--input",
type=str,
default="~/datasets/aishell3/train/normalized_wav",
help="path of the processed wav folder")
parser.add_argument(
"--output",
type=str,
default="~/datasets/aishell3/train/mel",
help="path of the folder to save mel spectrograms")
parser.add_argument(
"--opts",
nargs=argparse.REMAINDER,
help="options to overwrite --config file and the default config, passing in KEY VALUE pairs"
)
default_config = get_cfg_defaults()
args = parser.parse_args()
if args.config:
default_config.merge_from_file(args.config)
if args.opts:
default_config.merge_from_list(args.opts)
default_config.freeze()
audio_config = default_config.data
extract_mel_multispeaker(audio_config, args.input, args.output)