mirror of
https://github.com/k2-fsa/icefall.git
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140 lines
3.5 KiB
Python
140 lines
3.5 KiB
Python
#!/usr/bin/env python3
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# Copyright 2021 Xiaomi Corp. (authors: Fangjun Kuang)
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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 script takes as input lang_dir and generates HLG from
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- L, the lexicon, built from lang_dir/L_disambig.pt
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Caution: We use a lexicon that contains disambiguation symbols
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- G, the LM, built from data/lm/G_3_gram.fst.txt
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The generated LG is saved in $lang_dir/LG.fst
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"""
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import argparse
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import logging
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from pathlib import Path
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import k2
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import kaldifst
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import torch
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from kaldifst.utils import k2_to_openfst
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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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"--lang-dir",
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type=str,
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help="""Input and output directory.
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""",
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)
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return parser.parse_args()
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def compile_LG(lang_dir: str) -> kaldifst.StdVectorFst:
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"""
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Args:
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lang_dir:
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The language directory, e.g., data/lang_phone or data/lang_bpe_500.
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Return:
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An FST representing LG.
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"""
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tokens = kaldifst.SymbolTable.read_text(f"{lang_dir}/tokens.txt")
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words = kaldifst.SymbolTable.read_text(f"{lang_dir}/words.txt")
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assert "#0" in tokens
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assert "#0" in words
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token_disambig_id = tokens.find("#02")
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word_disambig_id = words.find("#0")
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L = k2.Fsa.from_dict(torch.load(f"{lang_dir}/L_disambig.pt"))
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L = k2_to_openfst(L, olabels="aux_labels")
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kaldifst.arcsort(L, sort_type="olabel")
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L.write(f"{lang_dir}/L.fst")
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with open("data/lm/G_3_gram.fst.txt") as f:
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G = kaldifst.compile(
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f.read(),
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acceptor=False,
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fst_type="vector",
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arc_type="standard",
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)
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kaldifst.arcsort(G, sort_type="ilabel")
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logging.info(f"Composing LG")
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LG = kaldifst.compose(
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L,
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G,
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match_side="left",
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compose_filter="sequence",
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connect=True,
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)
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logging.info(f"Determinize star LG")
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kaldifst.determinize_star(LG)
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logging.info(f"minimizeencoded")
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kaldifst.minimize_encoded(LG)
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# Set all disambig IDs to eps
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for state in kaldifst.StateIterator(LG):
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for arc in kaldifst.ArcIterator(LG, state):
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if arc.ilabel >= token_disambig_id:
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arc.ilabel = 0
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if arc.olabel >= word_disambig_id:
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arc.olabel = 0
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# reset properties as we changed the arc labels above
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LG.properties(0xFFFFFFFF, True)
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return LG
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def main():
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args = get_args()
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lang_dir = Path(args.lang_dir)
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out_filename = lang_dir / "LG.fst"
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if out_filename.is_file():
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logging.info(f"{out_filename} already exists - skipping")
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return
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logging.info(f"Processing {lang_dir}")
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LG = compile_LG(lang_dir)
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logging.info(f"Saving LG to {out_filename}")
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LG.write(str(out_filename))
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if __name__ == "__main__":
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formatter = (
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"%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"
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)
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logging.basicConfig(format=formatter, level=logging.INFO)
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main()
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