MockingBird/synthesizer_preprocess_audio.py

65 lines
3.0 KiB
Python

from synthesizer.preprocess import preprocess_dataset
from synthesizer.hparams import hparams
from utils.argutils import print_args
from pathlib import Path
import argparse
recognized_datasets = [
"aidatatang_200zh",
"magicdata",
"aishell3"
]
if __name__ == "__main__":
print("This method is deprecaded and will not be longer supported, please use 'pre.py'")
parser = argparse.ArgumentParser(
description="Preprocesses audio files from datasets, encodes them as mel spectrograms "
"and writes them to the disk. Audio files are also saved, to be used by the "
"vocoder for training.",
formatter_class=argparse.ArgumentDefaultsHelpFormatter
)
parser.add_argument("datasets_root", type=Path, help=\
"Path to the directory containing your LibriSpeech/TTS datasets.")
parser.add_argument("-o", "--out_dir", type=Path, default=argparse.SUPPRESS, help=\
"Path to the output directory that will contain the mel spectrograms, the audios and the "
"embeds. Defaults to <datasets_root>/SV2TTS/synthesizer/")
parser.add_argument("-n", "--n_processes", type=int, default=None, help=\
"Number of processes in parallel.")
parser.add_argument("-s", "--skip_existing", action="store_true", help=\
"Whether to overwrite existing files with the same name. Useful if the preprocessing was "
"interrupted.")
parser.add_argument("--hparams", type=str, default="", help=\
"Hyperparameter overrides as a comma-separated list of name-value pairs")
parser.add_argument("--no_trim", action="store_true", help=\
"Preprocess audio without trimming silences (not recommended).")
parser.add_argument("--no_alignments", action="store_true", help=\
"Use this option when dataset does not include alignments\
(these are used to split long audio files into sub-utterances.)")
parser.add_argument("--dataset", type=str, default="aidatatang_200zh", help=\
"Name of the dataset to process, allowing values: magicdata, aidatatang_200zh.")
args = parser.parse_args()
# Process the arguments
if not hasattr(args, "out_dir"):
args.out_dir = args.datasets_root.joinpath("SV2TTS", "synthesizer")
assert args.dataset in recognized_datasets, 'is not supported, please vote for it in https://github.com/babysor/MockingBird/issues/10'
# Create directories
assert args.datasets_root.exists()
args.out_dir.mkdir(exist_ok=True, parents=True)
# Verify webrtcvad is available
if not args.no_trim:
try:
import webrtcvad
except:
raise ModuleNotFoundError("Package 'webrtcvad' not found. This package enables "
"noise removal and is recommended. Please install and try again. If installation fails, "
"use --no_trim to disable this error message.")
del args.no_trim
# Preprocess the dataset
print_args(args, parser)
args.hparams = hparams.parse(args.hparams)
preprocess_dataset(**vars(args))