import os import re import cn2an from pypinyin import lazy_pinyin, Style # from text.symbols import punctuation from .symbols import language_tone_start_map from .tone_sandhi import ToneSandhi from .english import g2p as g2p_en from transformers import AutoTokenizer punctuation = ["!", "?", "…", ",", ".", "'", "-"] 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.posseg as psg 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_a-zA-Z\s" + "".join(punctuation) + r"]+", "", replaced_text) replaced_text = re.sub(r"[\s]+", " ", replaced_text) return replaced_text def g2p(text, impl='v2'): pattern = r"(?<=[{0}])\s*".format("".join(punctuation)) sentences = [i for i in re.split(pattern, text) if i.strip() != ""] if impl == 'v1': _func = _g2p elif impl == 'v2': _func = _g2p_v2 else: raise NotImplementedError() phones, tones, word2ph = _func(sentences) assert sum(word2ph) == len(phones) # assert len(word2ph) == len(text) # Sometimes it will crash,you can add a try-catch. phones = ["_"] + phones + ["_"] tones = [0] + tones + [0] word2ph = [1] + word2ph + [1] return phones, tones, 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 model_id = 'bert-base-multilingual-uncased' tokenizer = AutoTokenizer.from_pretrained(model_id) def _g2p(segments): phones_list = [] tones_list = [] word2ph = [] for seg in segments: # Replace all English words in the sentence # seg = re.sub("[a-zA-Z]+", "", seg) seg_cut = psg.lcut(seg) initials = [] finals = [] seg_cut = tone_modifier.pre_merge_for_modify(seg_cut) for word, pos in seg_cut: if pos == "eng": initials.append(['EN_WORD']) finals.append([word]) else: sub_initials, sub_finals = _get_initials_finals(word) sub_finals = tone_modifier.modified_tone(word, pos, sub_finals) initials.append(sub_initials) finals.append(sub_finals) # assert len(sub_initials) == len(sub_finals) == len(word) initials = sum(initials, []) finals = sum(finals, []) # for c, v in zip(initials, finals): if c == 'EN_WORD': tokenized_en = tokenizer.tokenize(v) phones_en, tones_en, word2ph_en = g2p_en(text=None, pad_start_end=False, tokenized=tokenized_en) # apply offset to tones_en tones_en = [t + language_tone_start_map['EN'] for t in tones_en] phones_list += phones_en tones_list += tones_en word2ph += word2ph_en else: 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] tone = "0" 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) phone = pinyin_to_symbol_map[pinyin].split(" ") word2ph.append(len(phone)) phones_list += phone tones_list += [int(tone)] * len(phone) return phones_list, tones_list, word2ph def text_normalize(text): numbers = re.findall(r"\d+(?:\.?\d+)?", text) for number in numbers: text = text.replace(number, cn2an.an2cn(number), 1) text = replace_punctuation(text) return text def get_bert_feature(text, word2ph, device): from . import chinese_bert return chinese_bert.get_bert_feature(text, word2ph, model_id='bert-base-multilingual-uncased', device=device) from .chinese import _g2p as _chinese_g2p def _g2p_v2(segments): spliter = '#$&^!@' phones_list = [] tones_list = [] word2ph = [] for text in segments: assert spliter not in text # replace all english words text = re.sub('([a-zA-Z\s]+)', lambda x: f'{spliter}{x.group(1)}{spliter}', text) texts = text.split(spliter) texts = [t for t in texts if len(t) > 0] for text in texts: if re.match('[a-zA-Z\s]+', text): # english tokenized_en = tokenizer.tokenize(text) phones_en, tones_en, word2ph_en = g2p_en(text=None, pad_start_end=False, tokenized=tokenized_en) # apply offset to tones_en tones_en = [t + language_tone_start_map['EN'] for t in tones_en] phones_list += phones_en tones_list += tones_en word2ph += word2ph_en else: phones_zh, tones_zh, word2ph_zh = _chinese_g2p([text]) phones_list += phones_zh tones_list += tones_zh word2ph += word2ph_zh return phones_list, tones_list, word2ph if __name__ == "__main__": # from text.chinese_bert import get_bert_feature text = "NFT啊！chemistry 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 = '我最近在学习machine learning，希望能够在未来的artificial intelligence领域有所建树。' text = '今天下午，我们准备去shopping mall购物，然后晚上去看一场movie。' text = '我们现在 also 能够 help 很多公司 use some machine learning 的 algorithms 啊!' text = text_normalize(text) print(text) phones, tones, word2ph = g2p(text, impl='v2') bert = get_bert_feature(text, word2ph, device='cuda:0') print(phones) import pdb; pdb.set_trace() # # 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