# -*- coding: utf-8 -*- # This project combines the TN and G2P functions of https://github.com/RVC-Boss/GPT-SoVITS and https://github.com/wenet-e2e/WeTextProcessing # Huawei Technologies Co., Ltd. (authors: Xiao Chen) from text.cleaner import clean_text import LangSegment from text import symbols as symbols_v1 from TN_processors import punct_normalization, MultilingualTN, alphabet_normalization import sys class BaseG2P: def __init__(self): self.sil_symbol = '[SIL]' self.comma_symbol = '[CM]' # , self.peroid_symbol = '[PD]' # . self.question_symbol = '[QN]' # ? self.exclamation_symbol = '[EX]' # ! self.punct_to_symbol = {',': self.comma_symbol, '.': self.peroid_symbol, '!': self.exclamation_symbol, '?': self.question_symbol} self.er_mapping = {'er1': ('e1', 'rr'), 'er2': ('e2', 'rr'), 'er3': ('e3', 'rr'), 'er4': ('e4', 'rr'), 'er5': ('e5', 'rr'), 'r5': ('e5', 'rr')} pass def replace_punct_with_symbol(self, phone_list): rep_list = [] for ph in phone_list: if ph in self.punct_to_symbol: rep_list.append(self.punct_to_symbol[ph]) else: rep_list.append(ph) return rep_list class MultilingualG2P(BaseG2P): def __init__(self, module="wenet", remove_interjections=False, remove_erhua=True): BaseG2P.__init__(self) self.tn_module = module self.language_module_map = {"zh": "chinese", "en": "english"} self.version = "v1" self.output_eng_word_boundary = False self.output_chn_word_boundary = False if self.tn_module == "wenet": self.tn_wenet = MultilingualTN("wenet", remove_interjections, remove_erhua) return def set_output_eng_word_boundary(self, output_eng_word_boundary): self.output_eng_word_boundary = output_eng_word_boundary def set_output_chn_word_boundary(self, output_chn_word_boundary): self.output_chn_word_boundary = output_chn_word_boundary def g2p_for_norm_text(self, norm_text, language): symbols = symbols_v1.symbols if(language not in self.language_module_map): language="zh" text=" " language_module = __import__("text."+self.language_module_map[language],fromlist=[self.language_module_map[language]]) if language == "zh":########## phones, word2ph = language_module.g2p(norm_text) assert len(phones) == sum(word2ph) assert len(norm_text) == len(word2ph) elif language == "en": if self.output_eng_word_boundary: phones = language_module.g2p_with_boundary(norm_text) else: phones = language_module.g2p(norm_text) # if len(phones) < 4: # phones = [','] + phones word2ph = None else: phones = language_module.g2p(norm_text) word2ph = None phones = ['UNK' if ph not in symbols else ph for ph in phones] return phones, word2ph def text_normalization_and_g2p(self, text, language, with_lang_prefix=False, normalize_punct=False): ''' language in {en, zh}, if language == "zh", this method supports mixture of English and Chinese input. if language == "en", this method only supports English input. ''' if normalize_punct: text = punct_normalization(text) # print('norm text: ' + text) text = alphabet_normalization(text) text = text.lower() if language in {"en"}: language = language.replace("all_", "") if language == "en": LangSegment.setfilters(["en"]) formattext = " ".join(tmp["text"] for tmp in LangSegment.getTexts(text)) else: # 因无法区别中日韩文汉字,以用户输入为准 formattext = text while " " in formattext: formattext = formattext.replace(" ", " ") if self.tn_module == "baidu": phones, word2ph, norm_text = clean_text( formattext, language, self.version) all_norm_text = norm_text else: norm_formattext = self.tn_wenet.normalize_segment(formattext, language, normalize_punct) phones, word2ph = self.g2p_for_norm_text(norm_formattext, language) all_norm_text = norm_formattext elif language in {"zh", "auto"}: textlist = [] langlist = [] LangSegment.setfilters(["en", "zh", "ja", "ko"]) # priority_lang = LangSegment.getfilters() if language == "auto": for tmp in LangSegment.getTexts(text): langlist.append(tmp["lang"]) textlist.append(tmp["text"]) else: for tmp in LangSegment.getTexts(text): if tmp["lang"] == "en": langlist.append(tmp["lang"]) else: # 因无法区别中日韩文汉字,以用户输入为准 langlist.append(language) textlist.append(tmp["text"]) #fix consecutive segment of same language mergelist = [] for idx in range(len(textlist)): if idx > 0 and langlist[idx - 1] == langlist[idx]: mergelist.append(1) else: mergelist.append(0) merged_textlist = [] merged_langlist = [] for idx in range(len(mergelist)): if mergelist[idx] == 0: merged_textlist.append(textlist[idx]) merged_langlist.append(langlist[idx]) else: merged_textlist[-1] += " " + textlist[idx] textlist = merged_textlist langlist = merged_langlist assert len(textlist) == len(langlist) # print(textlist) # print(langlist) phones_list = [] norm_text_list = [] for i in range(len(textlist)): lang = langlist[i] if self.tn_module == "wenet": norm_text = self.tn_wenet.normalize_segment(textlist[i], lang, normalize_punct) phones, word2ph = self.g2p_for_norm_text(norm_text, lang) else: phones, word2ph, norm_text = clean_text( textlist[i], lang, self.version) # lang prefix is only for mix language if with_lang_prefix: phones_with_lang = [] for ph in phones: if ph[0].isalpha(): phones_with_lang.append(lang + '_' + ph) else: phones_with_lang.append(ph) phones_list.append(phones_with_lang) else: phones_list.append(phones) norm_text_list.append(norm_text) phones = sum(phones_list, []) all_norm_text = ' '.join(norm_text_list) # if not final and len(phones) < 6: # return text_normalization_and_g2p("." + text,language,version,final=True) if normalize_punct: phones = self.replace_punct_with_symbol(phones) return phones, all_norm_text if __name__ == '__main__': ''' Testing functions ''' # text = '1983年2月，旅行了2天的儿童和长翅膀的女孩儿：“︘菜单修订后有鱼香肉丝儿、『王道椒香鸡腿〕和川蜀鸡翅？……”it\'s a test 112.王会计会计算机。which had been in force since 1760.调查员决定调节调查的难度。Article VI, Qing government would be charged an annual interest rate of 5% for the money.√2和π是不是无理数？' # text = '马打兰王国（732-1006），是8世纪到10世纪期间，存在于中爪哇的一个印度化王国。' language = 'zh' # zh means the model treats all non-English as Chinese, en means the model treats all langauge as English. mG2P = MultilingualG2P("wenet", remove_interjections=False, remove_erhua=False) # 'baidu' or 'wenet' mG2P.set_output_eng_word_boundary(True) sys.stdout.write("Input: ") sys.stdout.flush() for line in sys.stdin: if line.strip() == "exit()": exit() if len(line.strip()) <= 0: sys.stdout.write("Input: ") sys.stdout.flush() continue phones, norm_text = mG2P.text_normalization_and_g2p( line.strip(), language, with_lang_prefix=True, normalize_punct=True) sys.stdout.write("Norm Text: " + norm_text + "\n") sys.stdout.write("phonemes: " + " ".join(phones) + "\n") sys.stdout.write("Input: ") sys.stdout.flush()