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96 lines
3.3 KiB
96 lines
3.3 KiB
3 years ago
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# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import argparse
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import multiprocessing as mp
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from functools import partial
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from pathlib import Path
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import numpy as np
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import tqdm
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3 years ago
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from paddlespeech.t2s.audio import AudioProcessor
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from paddlespeech.t2s.audio.spec_normalizer import LogMagnitude
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from paddlespeech.t2s.audio.spec_normalizer import NormalizerBase
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from paddlespeech.t2s.exps.voice_cloning.tacotron2_ge2e.config import get_cfg_defaults
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3 years ago
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def extract_mel(fname: Path,
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input_dir: Path,
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output_dir: Path,
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p: AudioProcessor,
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n: NormalizerBase):
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relative_path = fname.relative_to(input_dir)
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out_path = (output_dir / relative_path).with_suffix(".npy")
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out_path.parent.mkdir(parents=True, exist_ok=True)
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wav = p.read_wav(fname)
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mel = p.mel_spectrogram(wav)
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mel = n.transform(mel)
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np.save(out_path, mel)
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def extract_mel_multispeaker(config, input_dir, output_dir, extension=".wav"):
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input_dir = Path(input_dir).expanduser()
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fnames = list(input_dir.rglob(f"*{extension}"))
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output_dir = Path(output_dir).expanduser()
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output_dir.mkdir(parents=True, exist_ok=True)
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p = AudioProcessor(config.sample_rate, config.n_fft, config.win_length,
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3 years ago
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config.hop_length, config.d_mels, config.fmin,
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3 years ago
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config.fmax)
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n = LogMagnitude(1e-5)
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func = partial(
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extract_mel, input_dir=input_dir, output_dir=output_dir, p=p, n=n)
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with mp.Pool(16) as pool:
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list(
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tqdm.tqdm(
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pool.imap(func, fnames), total=len(fnames), unit="utterance"))
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(
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description="Extract mel spectrogram from processed wav in AiShell3 training dataset."
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)
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parser.add_argument(
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"--config",
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type=str,
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help="yaml config file to overwrite the default config")
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parser.add_argument(
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"--input",
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type=str,
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default="~/datasets/aishell3/train/normalized_wav",
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help="path of the processed wav folder")
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parser.add_argument(
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"--output",
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type=str,
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default="~/datasets/aishell3/train/mel",
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help="path of the folder to save mel spectrograms")
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parser.add_argument(
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"--opts",
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nargs=argparse.REMAINDER,
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help="options to overwrite --config file and the default config, passing in KEY VALUE pairs"
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)
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default_config = get_cfg_defaults()
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args = parser.parse_args()
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if args.config:
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default_config.merge_from_file(args.config)
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if args.opts:
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default_config.merge_from_list(args.opts)
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default_config.freeze()
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audio_config = default_config.data
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extract_mel_multispeaker(audio_config, args.input, args.output)
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