51 lines
1.1 KiB
Python
51 lines
1.1 KiB
Python
import argparse
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import random
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import string
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from functools import cache
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from pathlib import Path
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import torch
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from g2p_en import G2p
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from tqdm import tqdm
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@cache
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def _get_model():
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return G2p()
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@cache
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def _get_graphs(path):
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with open(path, "r") as f:
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graphs = f.read()
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return graphs
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def encode(graphs: str) -> list[str]:
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g2p = _get_model()
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phones = g2p(graphs)
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ignored = {" ", *string.punctuation}
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return ["_" if p in ignored else p for p in phones]
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@torch.no_grad()
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument("folder", type=Path)
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parser.add_argument("--suffix", type=str, default=".normalized.txt")
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args = parser.parse_args()
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paths = list(args.folder.rglob(f"*{args.suffix}"))
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random.shuffle(paths)
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for path in tqdm(paths):
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phone_path = path.with_name(path.stem.split(".")[0] + ".phn.txt")
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graphs = _get_graphs(path)
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phones = encode(graphs)
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with open(phone_path, "w") as f:
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f.write(" ".join(phones))
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if __name__ == "__main__":
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main()
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