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| from . import chinese, japanese, english, chinese_mix, korean, french, spanish | |
| from . import cleaned_text_to_sequence | |
| import copy | |
| language_module_map = {"ZH": chinese, "JP": japanese, "EN": english, 'ZH_MIX_EN': chinese_mix, '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_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 |