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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_mix as language_module
elif language == "EN":
from . import english as language_module
elif language == "JP":
from . import japanese as language_module
elif language == "KR":
from . import korean as language_module
elif language == "FR":
from . import french as language_module
elif language == "SP" or language == "ES":
from . import spanish 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 |