| import time | |
| from . import cleaned_text_to_sequence | |
| import copy | |
| # language_module_map = {"ZH": chinese, | |
| # 'ZH_MIX_EN': chinese_mix, | |
| # "EN": english, | |
| # "JP": japanese} | |
| # 'KR': korean, | |
| # 'FR': french, | |
| # 'SP': spanish, | |
| # 'ES': spanish, | |
| # } | |
| # def clean_text(text, language): | |
| # language_module = language_module_map[language] | |
| # norm_text = language_module.text_normalize(text) | |
| # phones, tones, word2ph = language_module.g2p(norm_text) | |
| # return norm_text, phones, tones, word2ph | |
| def clean_text(text, language): | |
| start = time.time() | |
| if language == "ZH": | |
| from .import chinese as language_module | |
| elif language == "ZH_MIX_EN": | |
| from .import chinese_bert as language_module | |
| elif language == "EN": | |
| from .import english as language_module | |
| elif language == "JP": | |
| from .import japanese as language_module | |
| else: | |
| assert False, f"Unsupported lanuguage: {language}" | |
| print(f"Load language module take {1000 * (time.time() - start)}ms") | |
| norm_text = language_module.text_normalize(text) | |
| phones, tones, word2ph = language_module.g2p(norm_text) | |
| return norm_text, phones, tones, word2ph | |
| # def clean_text_bert(text, language, device=None): | |
| # language_module = language_module_map[language] | |
| # norm_text = language_module.text_normalize(text) | |
| # phones, tones, word2ph = language_module.g2p(norm_text) | |
| # word2ph_bak = copy.deepcopy(word2ph) | |
| # for i in range(len(word2ph)): | |
| # word2ph[i] = word2ph[i] * 2 | |
| # word2ph[0] += 1 | |
| # bert = language_module.get_bert_feature(norm_text, word2ph, device=device) | |
| # return norm_text, phones, tones, word2ph_bak, bert | |
| def text_to_sequence(text, language): | |
| norm_text, phones, tones, word2ph = clean_text(text, language) | |
| return cleaned_text_to_sequence(phones, tones, language) | |
| if __name__ == "__main__": | |
| pass |