mirror of
https://github.com/k2-fsa/icefall.git
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117 lines
3.3 KiB
Python
Executable File
117 lines
3.3 KiB
Python
Executable File
#!/usr/bin/env python3
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# Copyright 2023 Xiaomi Corp. (authors: Zengwei Yao)
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#
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# See ../../../../LICENSE for clarification regarding multiple authors
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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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"""
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This file reads the texts in given manifest and generate the file that maps tokens to IDs.
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"""
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import argparse
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import logging
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from collections import Counter
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from pathlib import Path
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from typing import Dict
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import g2p_en
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import tacotron_cleaner.cleaners
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from lhotse import load_manifest
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def get_args():
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parser = argparse.ArgumentParser()
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parser.add_argument(
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"--manifest-file",
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type=Path,
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default=Path("data/spectrogram/ljspeech_cuts_train.jsonl.gz"),
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help="Path to the manifest file",
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)
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parser.add_argument(
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"--tokens",
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type=Path,
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default=Path("data/tokens.txt"),
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help="Path to the tokens",
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)
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return parser.parse_args()
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def write_mapping(filename: str, sym2id: Dict[str, int]) -> None:
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"""Write a symbol to ID mapping to a file.
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Note:
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No need to implement `read_mapping` as it can be done
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through :func:`k2.SymbolTable.from_file`.
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Args:
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filename:
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Filename to save the mapping.
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sym2id:
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A dict mapping symbols to IDs.
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Returns:
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Return None.
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"""
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with open(filename, "w", encoding="utf-8") as f:
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for sym, i in sym2id.items():
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f.write(f"{sym} {i}\n")
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def get_token2id(manifest_file: Path) -> Dict[str, int]:
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"""Return a dict that maps token to IDs."""
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extra_tokens = {
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"<blk>": 0, # blank
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"<sos/eos>": 1, # sos and eos symbols.
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"<unk>": 2, # OOV
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}
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cut_set = load_manifest(manifest_file)
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g2p = g2p_en.G2p()
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counter = Counter()
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for cut in cut_set:
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# Each cut only contain one supervision
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assert len(cut.supervisions) == 1, len(cut.supervisions)
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text = cut.supervisions[0].normalized_text
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# Text normalization
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text = tacotron_cleaner.cleaners.custom_english_cleaners(text)
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# Convert to phonemes
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tokens = g2p(text)
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for t in tokens:
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counter[t] += 1
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# Sort by the number of occurrences in descending order
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tokens_and_counts = sorted(counter.items(), key=lambda x: -x[1])
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for token, idx in extra_tokens.items():
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tokens_and_counts.insert(idx, (token, None))
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token2id: Dict[str, int] = {token: i for i, (token, count) in enumerate(tokens_and_counts)}
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return token2id
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if __name__ == "__main__":
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formatter = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"
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logging.basicConfig(format=formatter, level=logging.INFO)
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args = get_args()
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manifest_file = Path(args.manifest_file)
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out_file = Path(args.tokens)
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token2id = get_token2id(manifest_file)
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write_mapping(out_file, token2id)
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