synthesizer_preprocess_audio.py

from synthesizer.preprocess import preprocess_librispeech, preprocess_SLR68, preprocess_SLR38, preprocess_aishell2
from synthesizer.hparams import hparams
from utils.argutils import print_args
from pathlib import Path
import argparse


if __name__ == "__main__":
    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("dataset", type=str,
                        help="Comma-separated list of the name of the dataset you want to preprocess. "
                        "Possible names: LibriSpeech, SLR68, SLR38, aishell2.")
    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("--detach_label_and_embed_utt", type=bool, default=False,
                        help="if True, use random utterance of the speaker to generate speaker embedding in synthesizer training.")
    args = parser.parse_args()

    # Process the arguments
    if not hasattr(args, "out_dir"):
        args.out_dir = args.datasets_root.joinpath("SV2TTS", "synthesizer")

    # Create directories
    assert args.datasets_root.exists()
    args.out_dir.mkdir(exist_ok=True, parents=True)

    # Preprocess the dataset
    print_args(args, parser)
    args.hparams = hparams.parse(args.hparams)

    preprocess_func = {
        "LibriSpeech": preprocess_librispeech,
        "SLR68": preprocess_SLR68,
        "SLR38": preprocess_SLR38,
        "aishell2": preprocess_aishell2,
    }
    print("Preprocessing %s" % args.dataset)
    assert args.dataset in preprocess_func, 'not surpport such dataset'
    preprocess_func[args.dataset](**vars(args))