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303 lines
8.5 KiB
303 lines
8.5 KiB
3 years ago
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# 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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from parakeet.frontend.phonectic import Phonetics
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"""
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A phonology system with ARPABET symbols and limited punctuations. The G2P
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conversion is done by g2p_en.
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Note that g2p_en does not handle words with hypen well. So make sure the input
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sentence is first normalized.
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"""
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from parakeet.frontend.vocab import Vocab
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from g2p_en import G2p
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class ARPABET(Phonetics):
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"""A phonology for English that uses ARPABET as the phoneme vocabulary.
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See http://www.speech.cs.cmu.edu/cgi-bin/cmudict for more details.
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Phoneme Example Translation
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------- ------- -----------
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AA odd AA D
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AE at AE T
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AH hut HH AH T
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AO ought AO T
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AW cow K AW
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AY hide HH AY D
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B be B IY
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CH cheese CH IY Z
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D dee D IY
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DH thee DH IY
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EH Ed EH D
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ER hurt HH ER T
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EY ate EY T
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F fee F IY
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G green G R IY N
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HH he HH IY
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IH it IH T
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IY eat IY T
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JH gee JH IY
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K key K IY
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L lee L IY
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M me M IY
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N knee N IY
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NG ping P IH NG
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OW oat OW T
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OY toy T OY
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P pee P IY
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R read R IY D
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S sea S IY
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SH she SH IY
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T tea T IY
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TH theta TH EY T AH
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UH hood HH UH D
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UW two T UW
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V vee V IY
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W we W IY
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Y yield Y IY L D
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Z zee Z IY
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ZH seizure S IY ZH ER
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"""
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phonemes = [
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'AA', 'AE', 'AH', 'AO', 'AW', 'AY', 'B', 'CH', 'D', 'DH', 'EH', 'ER',
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'EY', 'F', 'G', 'HH', 'IH', 'IY', 'JH', 'K', 'L', 'M', 'N', 'NG', 'OW',
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'OY', 'P', 'R', 'S', 'SH', 'T', 'TH', 'UW', 'UH', 'V', 'W', 'Y', 'Z',
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'ZH'
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]
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punctuations = [',', '.', '?', '!']
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symbols = phonemes + punctuations
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_stress_to_no_stress_ = {
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'AA0': 'AA',
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'AA1': 'AA',
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'AA2': 'AA',
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'AE0': 'AE',
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'AE1': 'AE',
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'AE2': 'AE',
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'AH0': 'AH',
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'AH1': 'AH',
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'AH2': 'AH',
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'AO0': 'AO',
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'AO1': 'AO',
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'AO2': 'AO',
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'AW0': 'AW',
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'AW1': 'AW',
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'AW2': 'AW',
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'AY0': 'AY',
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'AY1': 'AY',
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'AY2': 'AY',
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'EH0': 'EH',
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'EH1': 'EH',
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'EH2': 'EH',
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'ER0': 'ER',
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'ER1': 'ER',
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'ER2': 'ER',
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'EY0': 'EY',
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'EY1': 'EY',
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'EY2': 'EY',
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'IH0': 'IH',
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'IH1': 'IH',
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'IH2': 'IH',
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'IY0': 'IY',
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'IY1': 'IY',
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'IY2': 'IY',
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'OW0': 'OW',
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'OW1': 'OW',
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'OW2': 'OW',
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'OY0': 'OY',
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'OY1': 'OY',
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'OY2': 'OY',
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'UH0': 'UH',
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'UH1': 'UH',
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'UH2': 'UH',
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'UW0': 'UW',
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'UW1': 'UW',
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'UW2': 'UW'
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}
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def __init__(self):
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self.backend = G2p()
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self.vocab = Vocab(self.phonemes + self.punctuations)
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def _remove_vowels(self, phone):
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return self._stress_to_no_stress_.get(phone, phone)
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def phoneticize(self, sentence, add_start_end=False):
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""" Normalize the input text sequence and convert it into pronunciation sequence.
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Parameters
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-----------
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sentence: str
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The input text sequence.
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Returns
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----------
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List[str]
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The list of pronunciation sequence.
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"""
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phonemes = [
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self._remove_vowels(item) for item in self.backend(sentence)
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]
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if add_start_end:
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start = self.vocab.start_symbol
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end = self.vocab.end_symbol
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phonemes = [start] + phonemes + [end]
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phonemes = [item for item in phonemes if item in self.vocab.stoi]
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return phonemes
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def numericalize(self, phonemes):
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""" Convert pronunciation sequence into pronunciation id sequence.
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Parameters
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-----------
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phonemes: List[str]
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The list of pronunciation sequence.
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Returns
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----------
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List[int]
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The list of pronunciation id sequence.
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"""
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ids = [self.vocab.lookup(item) for item in phonemes]
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return ids
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def reverse(self, ids):
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""" Reverse the list of pronunciation id sequence to a list of pronunciation sequence.
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Parameters
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-----------
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ids: List[int]
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The list of pronunciation id sequence.
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Returns
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----------
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List[str]
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The list of pronunciation sequence.
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"""
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return [self.vocab.reverse(i) for i in ids]
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def __call__(self, sentence, add_start_end=False):
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""" Convert the input text sequence into pronunciation id sequence.
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Parameters
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-----------
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sentence: str
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The input text sequence.
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Returns
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----------
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List[str]
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The list of pronunciation id sequence.
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"""
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return self.numericalize(
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self.phoneticize(sentence, add_start_end=add_start_end))
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@property
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def vocab_size(self):
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""" Vocab size.
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"""
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# 47 = 39 phones + 4 punctuations + 4 special tokens
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return len(self.vocab)
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class ARPABETWithStress(Phonetics):
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phonemes = [
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'AA0', 'AA1', 'AA2', 'AE0', 'AE1', 'AE2', 'AH0', 'AH1', 'AH2', 'AO0',
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'AO1', 'AO2', 'AW0', 'AW1', 'AW2', 'AY0', 'AY1', 'AY2', 'B', 'CH', 'D',
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'DH', 'EH0', 'EH1', 'EH2', 'ER0', 'ER1', 'ER2', 'EY0', 'EY1', 'EY2',
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'F', 'G', 'HH', 'IH0', 'IH1', 'IH2', 'IY0', 'IY1', 'IY2', 'JH', 'K',
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'L', 'M', 'N', 'NG', 'OW0', 'OW1', 'OW2', 'OY0', 'OY1', 'OY2', 'P', 'R',
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'S', 'SH', 'T', 'TH', 'UH0', 'UH1', 'UH2', 'UW0', 'UW1', 'UW2', 'V',
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'W', 'Y', 'Z', 'ZH'
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]
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punctuations = [',', '.', '?', '!']
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symbols = phonemes + punctuations
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def __init__(self):
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self.backend = G2p()
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self.vocab = Vocab(self.phonemes + self.punctuations)
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def phoneticize(self, sentence, add_start_end=False):
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""" Normalize the input text sequence and convert it into pronunciation sequence.
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Parameters
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-----------
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sentence: str
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The input text sequence.
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Returns
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----------
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List[str]
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The list of pronunciation sequence.
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"""
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phonemes = self.backend(sentence)
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if add_start_end:
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start = self.vocab.start_symbol
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end = self.vocab.end_symbol
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phonemes = [start] + phonemes + [end]
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phonemes = [item for item in phonemes if item in self.vocab.stoi]
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return phonemes
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def numericalize(self, phonemes):
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""" Convert pronunciation sequence into pronunciation id sequence.
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Parameters
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-----------
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phonemes: List[str]
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The list of pronunciation sequence.
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Returns
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----------
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List[int]
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The list of pronunciation id sequence.
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"""
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ids = [self.vocab.lookup(item) for item in phonemes]
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return ids
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def reverse(self, ids):
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""" Reverse the list of pronunciation id sequence to a list of pronunciation sequence.
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Parameters
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-----------
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ids: List[int]
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The list of pronunciation id sequence.
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Returns
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----------
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List[str]
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The list of pronunciation sequence.
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"""
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return [self.vocab.reverse(i) for i in ids]
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def __call__(self, sentence, add_start_end=False):
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""" Convert the input text sequence into pronunciation id sequence.
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Parameters
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-----------
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sentence: str
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The input text sequence.
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Returns
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----------
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List[str]
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The list of pronunciation id sequence.
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"""
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return self.numericalize(
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self.phoneticize(sentence, add_start_end=add_start_end))
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@property
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def vocab_size(self):
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""" Vocab size.
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"""
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# 77 = 69 phones + 4 punctuations + 4 special tokens
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return len(self.vocab)
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