mirror of
https://github.com/k2-fsa/icefall.git
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79 lines
2.4 KiB
Python
Executable File
79 lines
2.4 KiB
Python
Executable File
#!/usr/bin/env python3
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# Copyright 2024 Xiaomi Corp. (authors: Yifan Yang)
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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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import gzip
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import json
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import re
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import sys
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from concurrent.futures.process import ProcessPoolExecutor
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from pathlib import Path
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from tn.english.normalizer import Normalizer as EnNormalizer
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from tqdm import tqdm
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from icefall.utils import str2bool
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class TextNormalizer:
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def __init__(self):
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self.en_tn_model = EnNormalizer(cache_dir="/tmp/tn", overwrite_cache=False)
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self.table = str.maketrans(
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"’‘，。；？！（）：-《》、“”【】", "'',.;?!(): <>/\"\"[]"
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)
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def __call__(self, cut):
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text = cut["supervisions"][0]["custom"]["texts"][0]
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# Process brackets
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text = re.sub(r"\([^\)]*\d[^\)]*\)", " ", text)
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text = re.sub(r"\([^\)]*\)", " ", text)
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# Apply mappings
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text = text.translate(self.table)
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# Remove extra spaces
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text = re.sub(r"\s+", " ", text).strip()
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text = self.en_tn_model.normalize(text)
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cut["supervisions"][0]["text"] = text
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del cut["supervisions"][0]["custom"]
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del cut["custom"]
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return cut
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# Assign text of the supervisions and remove unnecessary entries.
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def main():
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assert len(sys.argv) == 3, "Usage: ./local/prepare_manifest.py INPUT OUTPUT_DIR"
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fname = Path(sys.argv[1]).name
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oname = Path(sys.argv[2]) / fname
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tn = TextNormalizer()
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with ProcessPoolExecutor() as ex:
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with gzip.open(sys.argv[1], "r") as fin:
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cuts = (json.loads(line) for line in fin)
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results = ex.map(tn, cuts)
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with gzip.open(oname, "w") as fout:
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for cut in tqdm(results, desc="Processing"):
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fout.write((json.dumps(cut) + "\n").encode())
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if __name__ == "__main__":
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main()
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