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import pickle
import os
import re
from g2p_en import G2p
from bert_vits2.text import symbols
current_file_path = os.path.dirname(__file__)
CMU_DICT_PATH = os.path.join(current_file_path, 'cmudict.rep')
CACHE_PATH = os.path.join(current_file_path, 'cmudict_cache.pickle')
_g2p = G2p()
arpa = {'AH0', 'S', 'AH1', 'EY2', 'AE2', 'EH0', 'OW2', 'UH0', 'NG', 'B', 'G', 'AY0', 'M', 'AA0', 'F', 'AO0', 'ER2',
'UH1', 'IY1', 'AH2', 'DH', 'IY0', 'EY1', 'IH0', 'K', 'N', 'W', 'IY2', 'T', 'AA1', 'ER1', 'EH2', 'OY0', 'UH2',
'UW1', 'Z', 'AW2', 'AW1', 'V', 'UW2', 'AA2', 'ER', 'AW0', 'UW0', 'R', 'OW1', 'EH1', 'ZH', 'AE0', 'IH2', 'IH',
'Y', 'JH', 'P', 'AY1', 'EY0', 'OY2', 'TH', 'HH', 'D', 'ER0', 'CH', 'AO1', 'AE1', 'AO2', 'OY1', 'AY2', 'IH1',
'OW0', 'L', 'SH'}
def post_replace_ph(ph):
rep_map = {
'：': ',',
'；': ',',
'，': ',',
'。': '.',
'！': '!',
'？': '?',
'\n': '.',
"·": ",",
'、': ",",
'...': '…',
'v': "V"
}
if ph in rep_map.keys():
ph = rep_map[ph]
if ph in symbols:
return ph
if ph not in symbols:
ph = 'UNK'
return ph
def read_dict():
g2p_dict = {}
start_line = 49
with open(CMU_DICT_PATH) as f:
line = f.readline()
line_index = 1
while line:
if line_index >= start_line:
line = line.strip()
word_split = line.split(' ')
word = word_split[0]
syllable_split = word_split[1].split(' - ')
g2p_dict[word] = []
for syllable in syllable_split:
phone_split = syllable.split(' ')
g2p_dict[word].append(phone_split)
line_index = line_index + 1
line = f.readline()
return g2p_dict
def cache_dict(g2p_dict, file_path):
with open(file_path, 'wb') as pickle_file:
pickle.dump(g2p_dict, pickle_file)
def get_dict():
if os.path.exists(CACHE_PATH):
with open(CACHE_PATH, 'rb') as pickle_file:
g2p_dict = pickle.load(pickle_file)
else:
g2p_dict = read_dict()
cache_dict(g2p_dict, CACHE_PATH)
return g2p_dict
eng_dict = get_dict()
def refine_ph(phn):
tone = 0
if re.search(r'\d$', phn):
tone = int(phn[-1]) + 1
phn = phn[:-1]
return phn.lower(), tone
def refine_syllables(syllables):
tones = []
phonemes = []
for phn_list in syllables:
for i in range(len(phn_list)):
phn = phn_list[i]
phn, tone = refine_ph(phn)
phonemes.append(phn)
tones.append(tone)
return phonemes, tones
def text_normalize(text):
return text
def g2p(text):
phones = []
tones = []
words = re.split(r"([,;.\-\?\!\s+])", text)
for w in words:
if w.upper() in eng_dict:
phns, tns = refine_syllables(eng_dict[w.upper()])
phones += phns
tones += tns
else:
phone_list = list(filter(lambda p: p != " ", _g2p(w)))
for ph in phone_list:
if ph in arpa:
ph, tn = refine_ph(ph)
phones.append(ph)
tones.append(tn)
else:
phones.append(ph)
tones.append(0)
word2ph = [1 for i in phones]
phones = [post_replace_ph(i) for i in phones]
return phones, tones, word2ph
if __name__ == "__main__":
# print(get_dict())
# print(eng_word_to_phoneme("hello"))
print(g2p("In this paper, we propose 1 DSPGAN, a GAN-based universal vocoder."))
# all_phones = set()
# for k, syllables in eng_dict.items():
# for group in syllables:
# for ph in group:
# all_phones.add(ph)
# print(all_phones)
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