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import pickle
import os
import re
from . import symbols
from .fr_phonemizer import cleaner as fr_cleaner
from .fr_phonemizer import fr_to_ipa
from transformers import AutoTokenizer
def distribute_phone(n_phone, n_word):
phones_per_word = [0] * n_word
for task in range(n_phone):
min_tasks = min(phones_per_word)
min_index = phones_per_word.index(min_tasks)
phones_per_word[min_index] += 1
return phones_per_word
def text_normalize(text):
text = fr_cleaner.french_cleaners(text)
return text
model_id = 'dbmdz/bert-base-french-europeana-cased'
tokenizer = AutoTokenizer.from_pretrained(model_id)
def g2p(text, pad_start_end=True, tokenized=None):
if tokenized is None:
tokenized = tokenizer.tokenize(text)
# import pdb; pdb.set_trace()
phs = []
ph_groups = []
for t in tokenized:
if not t.startswith("#"):
ph_groups.append([t])
else:
ph_groups[-1].append(t.replace("#", ""))
phones = []
tones = []
word2ph = []
# print(ph_groups)
for group in ph_groups:
w = "".join(group)
phone_len = 0
word_len = len(group)
if w == '[UNK]':
phone_list = ['UNK']
else:
phone_list = list(filter(lambda p: p != " ", fr_to_ipa.fr2ipa(w)))
for ph in phone_list:
phones.append(ph)
tones.append(0)
phone_len += 1
aaa = distribute_phone(phone_len, word_len)
word2ph += aaa
# print(phone_list, aaa)
# print('=' * 10)
if pad_start_end:
phones = ["_"] + phones + ["_"]
tones = [0] + tones + [0]
word2ph = [1] + word2ph + [1]
return phones, tones, word2ph
def get_bert_feature(text, word2ph, device=None):
from text import french_bert
return french_bert.get_bert_feature(text, word2ph, device=device)
if __name__ == "__main__":
ori_text = 'Ce service gratuit est“”"" 【disponible》 en chinois 【simplifié] et autres 123'
# ori_text = "Ils essayaient vainement de faire comprendre à ma mère qu'avec les cent mille francs que m'avait laissé mon père,"
# print(ori_text)
text = text_normalize(ori_text)
print(text)
phoneme = fr_to_ipa.fr2ipa(text)
print(phoneme)
from TTS.tts.utils.text.phonemizers.multi_phonemizer import MultiPhonemizer
from text.cleaner_multiling import unicleaners
def text_normalize(text):
text = unicleaners(text, cased=True, lang='fr')
return text
# print(ori_text)
text = text_normalize(ori_text)
print(text)
phonemizer = MultiPhonemizer({"fr-fr": "espeak"})
# phonemizer.lang_to_phonemizer['fr'].keep_stress = True
# phonemizer.lang_to_phonemizer['fr'].use_espeak_phonemes = True
phoneme = phonemizer.phonemize(text, separator="", language='fr-fr')
print(phoneme) |