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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) |