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104 lines
3.8 KiB
104 lines
3.8 KiB
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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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 argparse
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from pathlib import Path
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from typing import List
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from typing import Union
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def erized(syllable: str) -> bool:
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"""Whether the syllable contains erhua effect.
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Example
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--------
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huar -> True
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guanr -> True
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er -> False
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"""
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# note: for pinyin, len(syllable) >=2 is always true
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# if not: there is something wrong in the data
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assert len(syllable) >= 2, f"inavlid syllable {syllable}"
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return syllable[:2] != "er" and syllable[-2] == 'r'
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def ignore_sandhi(reference: List[str], generated: List[str]) -> List[str]:
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"""
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Given a sequence of syllables from human annotation(reference),
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which makes sandhi explici and a sequence of syllables from some
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simple g2p program(generated), which does not consider sandhi,
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return a the reference sequence while ignore sandhi.
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Example
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--------
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['lao2', 'hu3'], ['lao3', 'hu3'] -> ['lao3', 'hu3']
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"""
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i = 0
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j = 0
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# sandhi ignored in the result while other errors are not included
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result = []
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while i < len(reference):
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if erized(reference[i]):
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result.append(reference[i])
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i += 1
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j += 2
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elif reference[i][:-1] == generated[i][:-1] and reference[i][
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-1] == '2' and generated[i][-1] == '3':
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result.append(generated[i])
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i += 1
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j += 1
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else:
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result.append(reference[i])
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i += 1
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j += 1
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assert j == len(
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generated
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), "length of transcriptions mismatch, There may be some characters that are ignored in the generated transcription."
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return result
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def convert_transcriptions(reference: Union[str, Path],
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generated: Union[str, Path],
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output: Union[str, Path]):
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with open(reference, 'rt') as f_ref:
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with open(generated, 'rt') as f_gen:
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with open(output, 'wt') as f_out:
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for i, (ref, gen) in enumerate(zip(f_ref, f_gen)):
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sentence_id, ref_transcription = ref.strip().split(' ', 1)
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_, gen_transcription = gen.strip().split(' ', 1)
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try:
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result = ignore_sandhi(ref_transcription.split(),
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gen_transcription.split())
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result = ' '.join(result)
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except Exception:
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print(
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f"sentence_id: {sentence_id} There is some annotation error in the reference or generated transcription. Use the reference."
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)
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result = ref_transcription
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f_out.write(f"{sentence_id} {result}\n")
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(
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description="reference transcription but ignore sandhi.")
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parser.add_argument(
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"--reference",
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type=str,
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help="path to the reference transcription of baker dataset.")
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parser.add_argument(
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"--generated", type=str, help="path to the generated transcription.")
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parser.add_argument("--output", type=str, help="path to save result.")
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args = parser.parse_args()
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convert_transcriptions(args.reference, args.generated, args.output)
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