icefall/egs/reazonspeech/ASR/local/prepare_lang_char.py
Triplecq 3b40d9bbb1
Zipformer recipe for ReazonSpeech (#1611)
* Add first cut at ReazonSpeech recipe

This recipe is mostly based on egs/csj, but tweaked to the point that
can be run with ReazonSpeech corpus.

Signed-off-by: Fujimoto Seiji <fujimoto@ceptord.net>

---------

Signed-off-by: Fujimoto Seiji <fujimoto@ceptord.net>
Co-authored-by: Fujimoto Seiji <fujimoto@ceptord.net>
Co-authored-by: Chen <qc@KDM00.cm.cluster>
Co-authored-by: root <root@KDA01.cm.cluster>
2024-06-13 14:19:03 +08:00

76 lines
2.1 KiB
Python

#!/usr/bin/env python3
# Copyright 2022 The University of Electro-Communications (Author: Teo Wen Shen) # noqa
#
# See ../../../../LICENSE for clarification regarding multiple authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import argparse
import logging
from pathlib import Path
from lhotse import CutSet
def get_args():
parser = argparse.ArgumentParser(
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
)
parser.add_argument(
"train_cut", metavar="train-cut", type=Path, help="Path to the train cut"
)
parser.add_argument(
"--lang-dir",
type=Path,
default=Path("data/lang_char"),
help=(
"Name of lang dir. "
"If not set, this will default to lang_char_{trans-mode}"
),
)
return parser.parse_args()
def main():
args = get_args()
logging.basicConfig(
format=("%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"),
level=logging.INFO,
)
sysdef_string = set(["<blk>", "<unk>", "<sos/eos>", " "])
token_set = set()
logging.info(f"Creating vocabulary from {args.train_cut}.")
train_cut: CutSet = CutSet.from_file(args.train_cut)
for cut in train_cut:
for sup in cut.supervisions:
token_set.update(sup.text)
token_set = ["<blk>"] + sorted(token_set - sysdef_string) + ["<unk>", "<sos/eos>"]
args.lang_dir.mkdir(parents=True, exist_ok=True)
(args.lang_dir / "tokens.txt").write_text(
"\n".join(f"{t}\t{i}" for i, t in enumerate(token_set))
)
(args.lang_dir / "lang_type").write_text("char")
logging.info("Done.")
if __name__ == "__main__":
main()