# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# 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.
"""
A phonology system with ARPABET symbols and limited punctuations. The G2P
conversion is done by g2p_en.
Note that g2p_en does not handle words with hypen well. So make sure the input
sentence is first normalized.
"""
from g2p_en import G2p
from paddlespeech.t2s.frontend.phonectic import Phonetics
from paddlespeech.t2s.frontend.vocab import Vocab
[docs]class ARPABET(Phonetics):
"""A phonology for English that uses ARPABET without stress as the phoneme vocabulary.
47 symbols = 39 phones + 4 punctuations + 4 special tokens(<pad> <unk> <s> </s>)
The current phoneme set contains 39 phonemes, vowels carry a lexical stress marker:
0 — No stress
1 — Primary stress
2 — Secondary stress
Phoneme Set:
Phoneme Example Translation
------- ------- -----------
AA odd AA D
AE at AE T
AH hut HH AH T
AO ought AO T
AW cow K AW
AY hide HH AY D
B be B IY
CH cheese CH IY Z
D dee D IY
DH thee DH IY
EH Ed EH D
ER hurt HH ER T
EY ate EY T
F fee F IY
G green G R IY N
HH he HH IY
IH it IH T
IY eat IY T
JH gee JH IY
K key K IY
L lee L IY
M me M IY
N knee N IY
NG ping P IH NG
OW oat OW T
OY toy T OY
P pee P IY
R read R IY D
S sea S IY
SH she SH IY
T tea T IY
TH theta TH EY T AH
UH hood HH UH D
UW two T UW
V vee V IY
W we W IY
Y yield Y IY L D
Z zee Z IY
ZH seizure S IY ZH ER
See http://www.speech.cs.cmu.edu/cgi-bin/cmudict for more details.
"""
# 39 phonemes
phonemes = [
'AA', 'AE', 'AH', 'AO', 'AW', 'AY', 'B', 'CH', 'D', 'DH', 'EH', 'ER',
'EY', 'F', 'G', 'HH', 'IH', 'IY', 'JH', 'K', 'L', 'M', 'N', 'NG', 'OW',
'OY', 'P', 'R', 'S', 'SH', 'T', 'TH', 'UW', 'UH', 'V', 'W', 'Y', 'Z',
'ZH'
]
punctuations = [',', '.', '?', '!']
symbols = phonemes + punctuations
# vowels carry a lexical stress marker：
# 0 unstressed（无重音）, 1 primary stress（主重音）和 2 secondary stress（次重音）
_stress_to_no_stress_ = {
'AA0': 'AA',
'AA1': 'AA',
'AA2': 'AA',
'AE0': 'AE',
'AE1': 'AE',
'AE2': 'AE',
'AH0': 'AH',
'AH1': 'AH',
'AH2': 'AH',
'AO0': 'AO',
'AO1': 'AO',
'AO2': 'AO',
'AW0': 'AW',
'AW1': 'AW',
'AW2': 'AW',
'AY0': 'AY',
'AY1': 'AY',
'AY2': 'AY',
'EH0': 'EH',
'EH1': 'EH',
'EH2': 'EH',
'ER0': 'ER',
'ER1': 'ER',
'ER2': 'ER',
'EY0': 'EY',
'EY1': 'EY',
'EY2': 'EY',
'IH0': 'IH',
'IH1': 'IH',
'IH2': 'IH',
'IY0': 'IY',
'IY1': 'IY',
'IY2': 'IY',
'OW0': 'OW',
'OW1': 'OW',
'OW2': 'OW',
'OY0': 'OY',
'OY1': 'OY',
'OY2': 'OY',
'UH0': 'UH',
'UH1': 'UH',
'UH2': 'UH',
'UW0': 'UW',
'UW1': 'UW',
'UW2': 'UW'
}
def __repr__(self):
fmt = "ARPABETWithoutStress(phonemes: {}, punctuations: {})"
return fmt.format(len(phonemes), punctuations)
def __init__(self):
# https://github.com/Kyubyong/g2p/blob/master/g2p_en/g2p.py
self.backend = G2p()
self.vocab = Vocab(self.phonemes + self.punctuations)
def _remove_vowels(self, phone):
return self._stress_to_no_stress_.get(phone, phone)
[docs] def phoneticize(self, sentence, add_start_end=False):
""" Normalize the input text sequence and convert it into pronunciation sequence.
Args:
sentence (str): The input text sequence.
Returns:
List[str]: The list of pronunciation sequence.
"""
# g2p and remove vowel stress
phonemes = [
self._remove_vowels(item) for item in self.backend(sentence)
]
if add_start_end:
start = self.vocab.start_symbol
end = self.vocab.end_symbol
phonemes = [start] + phonemes + [end]
phonemes = [item for item in phonemes if item in self.vocab.stoi]
return phonemes
[docs] def numericalize(self, phonemes):
""" Convert pronunciation sequence into pronunciation id sequence.
Args:
phonemes (List[str]): The list of pronunciation sequence.
Returns:
List[int]: The list of pronunciation id sequence.
"""
# phonemes to ids
ids = [self.vocab.lookup(item) for item in phonemes]
return ids
[docs] def reverse(self, ids):
""" Reverse the list of pronunciation id sequence to a list of pronunciation sequence.
Args:
ids( List[int]): The list of pronunciation id sequence.
Returns:
List[str]:
The list of pronunciation sequence.
"""
return [self.vocab.reverse(i) for i in ids]
def __call__(self, sentence, add_start_end=False):
""" Convert the input text sequence into pronunciation id sequence.
Args:
sentence (str): The input text sequence.
Returns:
List[str]: The list of pronunciation id sequence.
"""
return self.numericalize(
self.phoneticize(sentence, add_start_end=add_start_end))
@property
def vocab_size(self):
""" Vocab size.
"""
# 47 = 39 phones + 4 punctuations + 4 special tokens(<pad> <unk> <s> </s>)
return len(self.vocab)
[docs]class ARPABETWithStress(Phonetics):
"""
A phonology for English that uses ARPABET with stress as the phoneme vocabulary.
77 symbols = 69 phones + 4 punctuations + 4 special tokens
"""
phonemes = [
'AA0', 'AA1', 'AA2', 'AE0', 'AE1', 'AE2', 'AH0', 'AH1', 'AH2', 'AO0',
'AO1', 'AO2', 'AW0', 'AW1', 'AW2', 'AY0', 'AY1', 'AY2', 'B', 'CH', 'D',
'DH', 'EH0', 'EH1', 'EH2', 'ER0', 'ER1', 'ER2', 'EY0', 'EY1', 'EY2',
'F', 'G', 'HH', 'IH0', 'IH1', 'IH2', 'IY0', 'IY1', 'IY2', 'JH', 'K',
'L', 'M', 'N', 'NG', 'OW0', 'OW1', 'OW2', 'OY0', 'OY1', 'OY2', 'P', 'R',
'S', 'SH', 'T', 'TH', 'UH0', 'UH1', 'UH2', 'UW0', 'UW1', 'UW2', 'V',
'W', 'Y', 'Z', 'ZH'
]
punctuations = [',', '.', '?', '!']
symbols = phonemes + punctuations
def __repr__(self):
fmt = "ARPABETWithStress(phonemes: {}, punctuations: {})"
return fmt.format(len(phonemes), punctuations)
def __init__(self):
self.backend = G2p()
self.vocab = Vocab(self.phonemes + self.punctuations)
[docs] def phoneticize(self, sentence, add_start_end=False):
""" Normalize the input text sequence and convert it into pronunciation sequence.
Args:
sentence (str): The input text sequence.
Returns:
List[str]: The list of pronunciation sequence.
"""
phonemes = self.backend(sentence)
if add_start_end:
start = self.vocab.start_symbol
end = self.vocab.end_symbol
phonemes = [start] + phonemes + [end]
phonemes = [item for item in phonemes if item in self.vocab.stoi]
return phonemes
[docs] def numericalize(self, phonemes):
""" Convert pronunciation sequence into pronunciation id sequence.
Args:
phonemes (List[str]): The list of pronunciation sequence.
Returns:
List[int]: The list of pronunciation id sequence.
"""
ids = [self.vocab.lookup(item) for item in phonemes]
return ids
[docs] def reverse(self, ids):
""" Reverse the list of pronunciation id sequence to a list of pronunciation sequence.
Args:
ids (List[int]): The list of pronunciation id sequence.
Returns:
List[str]: The list of pronunciation sequence.
"""
return [self.vocab.reverse(i) for i in ids]
def __call__(self, sentence, add_start_end=False):
""" Convert the input text sequence into pronunciation id sequence.
Args:
sentence (str): The input text sequence.
Returns:
List[str]: The list of pronunciation id sequence.
"""
return self.numericalize(
self.phoneticize(sentence, add_start_end=add_start_end))
@property
def vocab_size(self):
""" Vocab size.
"""
# 77 = 69 phones + 4 punctuations + 4 special tokens
return len(self.vocab)