import os import pdb import re import cn2an from pypinyin import lazy_pinyin, Style from pypinyin.contrib.tone_convert import to_normal, to_finals_tone3, to_initials, to_finals from text.symbols import punctuation from text.tone_sandhi import ToneSandhi from text.zh_normalization.text_normlization import TextNormalizer normalizer = lambda x: cn2an.transform(x, "an2cn") current_file_path = os.path.dirname(__file__) pinyin_to_symbol_map = { line.split("\t")[0]: line.strip().split("\t")[1] for line in open(os.path.join(current_file_path, "opencpop-strict.txt")).readlines() } import jieba_fast.posseg as psg # is_g2pw_str = os.environ.get("is_g2pw", "True")##默认开启 # is_g2pw = False#True if is_g2pw_str.lower() == 'true' else False is_g2pw = True#True if is_g2pw_str.lower() == 'true' else False if is_g2pw: print("当前使用g2pw进行拼音推理") from text.g2pw import G2PWPinyin, correct_pronunciation parent_directory = os.path.dirname(current_file_path) g2pw = G2PWPinyin(model_dir="GPT_SoVITS/text/G2PWModel",model_source=os.environ.get("bert_path","GPT_SoVITS/pretrained_models/chinese-roberta-wwm-ext-large"),v_to_u=False, neutral_tone_with_five=True) rep_map = { ":": ",", ";": ",", ",": ",", "。": ".", "!": "!", "?": "?", "\n": ".", "·": ",", "、": ",", "...": "…", "$": ".", "/": ",", "—": "-", "~": "…", "~":"…", } tone_modifier = ToneSandhi() def replace_punctuation(text): text = text.replace("嗯", "恩").replace("呣", "母") pattern = re.compile("|".join(re.escape(p) for p in rep_map.keys())) replaced_text = pattern.sub(lambda x: rep_map[x.group()], text) replaced_text = re.sub( r"[^\u4e00-\u9fa5" + "".join(punctuation) + r"]+", "", replaced_text ) return replaced_text def g2p(text): pattern = r"(?<=[{0}])\s*".format("".join(punctuation)) sentences = [i for i in re.split(pattern, text) if i.strip() != ""] phones, word2ph = _g2p(sentences) return phones, word2ph def _get_initials_finals(word): initials = [] finals = [] orig_initials = lazy_pinyin(word, neutral_tone_with_five=True, style=Style.INITIALS) orig_finals = lazy_pinyin( word, neutral_tone_with_five=True, style=Style.FINALS_TONE3 ) for c, v in zip(orig_initials, orig_finals): initials.append(c) finals.append(v) return initials, finals must_erhua = { "小院儿", "胡同儿", "范儿", "老汉儿", "撒欢儿", "寻老礼儿", "妥妥儿", "媳妇儿" } not_erhua = { "虐儿", "为儿", "护儿", "瞒儿", "救儿", "替儿", "有儿", "一儿", "我儿", "俺儿", "妻儿", "拐儿", "聋儿", "乞儿", "患儿", "幼儿", "孤儿", "婴儿", "婴幼儿", "连体儿", "脑瘫儿", "流浪儿", "体弱儿", "混血儿", "蜜雪儿", "舫儿", "祖儿", "美儿", "应采儿", "可儿", "侄儿", "孙儿", "侄孙儿", "女儿", "男儿", "红孩儿", "花儿", "虫儿", "马儿", "鸟儿", "猪儿", "猫儿", "狗儿", "少儿" } def _merge_erhua(initials: list[str], finals: list[str], word: str, pos: str) -> list[list[str]]: """ Do erhub. """ # fix er1 for i, phn in enumerate(finals): if i == len(finals) - 1 and word[i] == "儿" and phn == 'er1': finals[i] = 'er2' # 发音 if word not in must_erhua and (word in not_erhua or pos in {"a", "j", "nr"}): return initials, finals # "……" 等情况直接返回 if len(finals) != len(word): return initials, finals assert len(finals) == len(word) # 与前一个字发同音 new_initials = [] new_finals = [] for i, phn in enumerate(finals): if i == len(finals) - 1 and word[i] == "儿" and phn in { "er2", "er5" } and word[-2:] not in not_erhua and new_finals: phn = "er" + new_finals[-1][-1] new_initials.append(initials[i]) new_finals.append(phn) return new_initials, new_finals def _g2p(segments): phones_list = [] word2ph = [] for seg in segments: pinyins = [] # Replace all English words in the sentence seg = re.sub("[a-zA-Z]+", "", seg) seg_cut = psg.lcut(seg) seg_cut = tone_modifier.pre_merge_for_modify(seg_cut) initials = [] finals = [] if not is_g2pw: for word, pos in seg_cut: if pos == "eng": continue sub_initials, sub_finals = _get_initials_finals(word) sub_finals = tone_modifier.modified_tone(word, pos, sub_finals) # 儿化 sub_initials, sub_finals = _merge_erhua(sub_initials, sub_finals, word, pos) initials.append(sub_initials) finals.append(sub_finals) # assert len(sub_initials) == len(sub_finals) == len(word) initials = sum(initials, []) finals = sum(finals, []) print("pypinyin结果",initials,finals) else: # g2pw采用整句推理 pinyins = g2pw.lazy_pinyin(seg, neutral_tone_with_five=True, style=Style.TONE3) pre_word_length = 0 for word, pos in seg_cut: sub_initials = [] sub_finals = [] now_word_length = pre_word_length + len(word) if pos == 'eng': pre_word_length = now_word_length continue word_pinyins = pinyins[pre_word_length:now_word_length] # 多音字消歧 word_pinyins = correct_pronunciation(word,word_pinyins) for pinyin in word_pinyins: if pinyin[0].isalpha(): sub_initials.append(to_initials(pinyin)) sub_finals.append(to_finals_tone3(pinyin,neutral_tone_with_five=True)) else: sub_initials.append(pinyin) sub_finals.append(pinyin) pre_word_length = now_word_length sub_finals = tone_modifier.modified_tone(word, pos, sub_finals) # 儿化 sub_initials, sub_finals = _merge_erhua(sub_initials, sub_finals, word, pos) initials.append(sub_initials) finals.append(sub_finals) initials = sum(initials, []) finals = sum(finals, []) # print("g2pw结果",initials,finals) for c, v in zip(initials, finals): raw_pinyin = c + v # NOTE: post process for pypinyin outputs # we discriminate i, ii and iii if c == v: assert c in punctuation phone = [c] word2ph.append(1) else: v_without_tone = v[:-1] tone = v[-1] pinyin = c + v_without_tone assert tone in "12345" if c: # 多音节 v_rep_map = { "uei": "ui", "iou": "iu", "uen": "un", } if v_without_tone in v_rep_map.keys(): pinyin = c + v_rep_map[v_without_tone] else: # 单音节 pinyin_rep_map = { "ing": "ying", "i": "yi", "in": "yin", "u": "wu", } if pinyin in pinyin_rep_map.keys(): pinyin = pinyin_rep_map[pinyin] else: single_rep_map = { "v": "yu", "e": "e", "i": "y", "u": "w", } if pinyin[0] in single_rep_map.keys(): pinyin = single_rep_map[pinyin[0]] + pinyin[1:] assert pinyin in pinyin_to_symbol_map.keys(), (pinyin, seg, raw_pinyin) new_c, new_v = pinyin_to_symbol_map[pinyin].split(" ") new_v = new_v + tone phone = [new_c, new_v] word2ph.append(len(phone)) phones_list += phone return phones_list, word2ph def replace_punctuation_with_en(text): text = text.replace("嗯", "恩").replace("呣", "母") pattern = re.compile("|".join(re.escape(p) for p in rep_map.keys())) replaced_text = pattern.sub(lambda x: rep_map[x.group()], text) replaced_text = re.sub( r"[^\u4e00-\u9fa5A-Za-z" + "".join(punctuation) + r"]+", "", replaced_text ) return replaced_text def replace_consecutive_punctuation(text): punctuations = ''.join(re.escape(p) for p in punctuation) pattern = f'([{punctuations}])([{punctuations}])+' result = re.sub(pattern, r'\1', text) return result def text_normalize(text): # https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/paddlespeech/t2s/frontend/zh_normalization tx = TextNormalizer() sentences = tx.normalize(text) dest_text = "" for sentence in sentences: dest_text += replace_punctuation(sentence) # 避免重复标点引起的参考泄露 dest_text = replace_consecutive_punctuation(dest_text) return dest_text # 不排除英文的文本格式化 def mix_text_normalize(text): # https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/paddlespeech/t2s/frontend/zh_normalization tx = TextNormalizer() sentences = tx.normalize(text) dest_text = "" for sentence in sentences: dest_text += replace_punctuation_with_en(sentence) # 避免重复标点引起的参考泄露 dest_text = replace_consecutive_punctuation(dest_text) return dest_text if __name__ == "__main__": text = "啊——但是《原神》是由,米哈\游自主,研发的一款全.新开放世界.冒险游戏" text = "呣呣呣~就是…大人的鼹鼠党吧?" text = "你好" text = text_normalize(text) print(g2p(text)) # # 示例用法 # text = "这是一个示例文本:,你好!这是一个测试..." # print(g2p_paddle(text)) # 输出: 这是一个示例文本你好这是一个测试