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| from synthesizer.preprocess import preprocess_librispeech, preprocess_vctk | |
| from synthesizer.hparams import syn_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("-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=4, 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("--datasets_names", type=list, default=["LibriSpeech","VCTK"], help=\ | |
| "Name of the dataset directory to process.") | |
| parser.add_argument("--all_subfolders", type=list, default=["train-clean-100,train-clean-360,dev-clean", "wav48_silence_trimmed"], help=\ | |
| "Comma-separated list of subfolders to process inside your dataset directory") | |
| 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 = syn_hparams.parse(args.hparams) | |
| preprocess_func = { | |
| "LibriSpeech": preprocess_librispeech, | |
| "VCTK": preprocess_vctk, | |
| } | |
| args = vars(args) | |
| for i in range(len(args["datasets_names"])): | |
| dataset = args["datasets_names"][i] | |
| subfolders = args["all_subfolders"][i] | |
| print("Preprocessing %s" % dataset) | |
| preprocess_func[dataset](datasets_root=args["datasets_root"], out_dir=args["out_dir"], n_processes=args["n_processes"], skip_existing=args["skip_existing"], hparams=args["hparams"], | |
| datasets_name=dataset, subfolders=subfolders) | |