f197177ae1
- FastAPI 백엔드: /api/voices, /api/tts, /api/health - 한국어 메인 + 영어(5종 악센트), 중국어/일본어 UI 제거 - 언어별 목소리 모델 선택, 속도(0.5~2.0x)/피치(±12반음) 조절 - 로그인/사용제한/과금 유도 없음 (무제한 테스트) - NVIDIA GPU 자동 사용 (torch cu128, Blackwell sm_120) - 유저 친화 한국어 UI (frontend) - Docker/compose (GPU 예약), 8788 포트 - MeloTTS(순수 파이썬) 벤더링 + 검증된 버전 고정(constraints)
94 lines
2.8 KiB
Python
94 lines
2.8 KiB
Python
import pickle
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import os
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import re
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from . import symbols
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from .fr_phonemizer import cleaner as fr_cleaner
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from .fr_phonemizer import fr_to_ipa
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from transformers import AutoTokenizer
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def distribute_phone(n_phone, n_word):
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phones_per_word = [0] * n_word
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for task in range(n_phone):
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min_tasks = min(phones_per_word)
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min_index = phones_per_word.index(min_tasks)
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phones_per_word[min_index] += 1
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return phones_per_word
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def text_normalize(text):
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text = fr_cleaner.french_cleaners(text)
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return text
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model_id = 'dbmdz/bert-base-french-europeana-cased'
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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def g2p(text, pad_start_end=True, tokenized=None):
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if tokenized is None:
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tokenized = tokenizer.tokenize(text)
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# import pdb; pdb.set_trace()
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phs = []
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ph_groups = []
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for t in tokenized:
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if not t.startswith("#"):
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ph_groups.append([t])
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else:
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ph_groups[-1].append(t.replace("#", ""))
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phones = []
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tones = []
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word2ph = []
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# print(ph_groups)
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for group in ph_groups:
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w = "".join(group)
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phone_len = 0
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word_len = len(group)
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if w == '[UNK]':
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phone_list = ['UNK']
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else:
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phone_list = list(filter(lambda p: p != " ", fr_to_ipa.fr2ipa(w)))
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for ph in phone_list:
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phones.append(ph)
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tones.append(0)
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phone_len += 1
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aaa = distribute_phone(phone_len, word_len)
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word2ph += aaa
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# print(phone_list, aaa)
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# print('=' * 10)
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if pad_start_end:
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phones = ["_"] + phones + ["_"]
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tones = [0] + tones + [0]
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word2ph = [1] + word2ph + [1]
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return phones, tones, word2ph
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def get_bert_feature(text, word2ph, device=None):
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from text import french_bert
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return french_bert.get_bert_feature(text, word2ph, device=device)
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if __name__ == "__main__":
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ori_text = 'Ce service gratuit est“”"" 【disponible》 en chinois 【simplifié] et autres 123'
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# ori_text = "Ils essayaient vainement de faire comprendre à ma mère qu'avec les cent mille francs que m'avait laissé mon père,"
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# print(ori_text)
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text = text_normalize(ori_text)
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print(text)
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phoneme = fr_to_ipa.fr2ipa(text)
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print(phoneme)
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from TTS.tts.utils.text.phonemizers.multi_phonemizer import MultiPhonemizer
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from text.cleaner_multiling import unicleaners
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def text_normalize(text):
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text = unicleaners(text, cased=True, lang='fr')
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return text
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# print(ori_text)
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text = text_normalize(ori_text)
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print(text)
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phonemizer = MultiPhonemizer({"fr-fr": "espeak"})
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# phonemizer.lang_to_phonemizer['fr'].keep_stress = True
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# phonemizer.lang_to_phonemizer['fr'].use_espeak_phonemes = True
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phoneme = phonemizer.phonemize(text, separator="", language='fr-fr')
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print(phoneme) |