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315 lines
8.4 KiB
315 lines
8.4 KiB
# Copyright (c) 2020 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 abc import ABC
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from abc import abstractmethod
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from g2p_en import G2p
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from g2pM import G2pM
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from parakeet.frontend.vocab import Vocab
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from parakeet.frontend.normalizer.normalizer import normalize
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from parakeet.frontend.punctuation import get_punctuations
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# discard opencc untill we find an easy solution to install it on windows
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# from opencc import OpenCC
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__all__ = ["Phonetics", "English", "EnglishCharacter", "Chinese"]
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class Phonetics(ABC):
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@abstractmethod
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def __call__(self, sentence):
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pass
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@abstractmethod
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def phoneticize(self, sentence):
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pass
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@abstractmethod
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def numericalize(self, phonemes):
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pass
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class English(Phonetics):
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""" Normalize the input text sequence and convert into pronunciation id sequence.
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"""
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def __init__(self):
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self.backend = G2p()
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self.phonemes = list(self.backend.phonemes)
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self.punctuations = get_punctuations("en")
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self.vocab = Vocab(self.phonemes + self.punctuations)
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def phoneticize(self, sentence):
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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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start = self.vocab.start_symbol
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end = self.vocab.end_symbol
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phonemes = ([] if start is None else [start]) \
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+ self.backend(sentence) \
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+ ([] if end is None else [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 = [
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self.vocab.lookup(item) for item in phonemes
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if item in self.vocab.stoi
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]
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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):
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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(self.phoneticize(sentence))
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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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return len(self.vocab)
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class EnglishCharacter(Phonetics):
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""" Normalize the input text sequence and convert it into character id sequence.
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"""
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def __init__(self):
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self.backend = G2p()
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self.graphemes = list(self.backend.graphemes)
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self.punctuations = get_punctuations("en")
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self.vocab = Vocab(self.graphemes + self.punctuations)
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def phoneticize(self, sentence):
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""" Normalize the input text 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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str
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A text sequence after normalize.
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"""
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words = normalize(sentence)
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return words
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def numericalize(self, sentence):
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""" Convert a text sequence into ids.
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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[int]
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List of a character id sequence.
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"""
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ids = [
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self.vocab.lookup(item) for item in sentence
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if item in self.vocab.stoi
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]
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return ids
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def reverse(self, ids):
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""" Convert a character id sequence into text.
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Parameters
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-----------
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ids: List[int]
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List of a character id sequence.
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Returns
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----------
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str
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The input text 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):
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""" Normalize the input text sequence and convert it into character 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[int]
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List of a character id sequence.
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"""
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return self.numericalize(self.phoneticize(sentence))
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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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return len(self.vocab)
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class Chinese(Phonetics):
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"""Normalize Chinese text sequence and convert it into ids.
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"""
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def __init__(self):
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# self.opencc_backend = OpenCC('t2s.json')
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self.backend = G2pM()
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self.phonemes = self._get_all_syllables()
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self.punctuations = get_punctuations("cn")
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self.vocab = Vocab(self.phonemes + self.punctuations)
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def _get_all_syllables(self):
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all_syllables = set([
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syllable for k, v in self.backend.cedict.items() for syllable in v
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])
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return list(all_syllables)
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def phoneticize(self, sentence):
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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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# simplified = self.opencc_backend.convert(sentence)
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simplified = sentence
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phonemes = self.backend(simplified)
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start = self.vocab.start_symbol
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end = self.vocab.end_symbol
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phonemes = ([] if start is None else [start]) \
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+ phonemes \
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+ ([] if end is None else [end])
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return self._filter_symbols(phonemes)
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def _filter_symbols(self, phonemes):
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cleaned_phonemes = []
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for item in phonemes:
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if item in self.vocab.stoi:
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cleaned_phonemes.append(item)
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else:
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for char in item:
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if char in self.vocab.stoi:
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cleaned_phonemes.append(char)
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return cleaned_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 __call__(self, sentence):
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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(self.phoneticize(sentence))
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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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return len(self.vocab)
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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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