def text_to_sequence(text, p=0.0):
#print("[Pabz-test] Frontend sin")
#if p >= 0:
# text = mix_pronunciation(text, p)
from deepvoice3_pytorch.frontend.text import text_to_sequence
text = text_to_sequence(text, ["english_cleaners"])
return text
def text_to_sequence(text, phonetic=None, p=0.0):
# 'text' = WordJTrans
# Called during train.py.
if (phonetic and p >= 0):
text = mix_pronunciation(text, phonetic, p)
from deepvoice3_pytorch.frontend.text import text_to_sequence
text = text_to_sequence(text, ["french_cleaners"])
return text
def text_to_sequence(text, p=0.0):
text = normalize_numbers(text)
text = text.replace('\r', '')
text = text + '.' if text[-1] not in '!,.:;?' else text
if p >= 0:
text = mix_pronunciation(text, p)
from deepvoice3_pytorch.frontend.text import text_to_sequence
text = text_to_sequence(text, ["english_cleaners"])
return text
def text_to_sequence(text, p=0.0):
from deepvoice3_pytorch.frontend.text import text_to_sequence
text = text_to_sequence(text, ["transliteration_cleaners"])
return text
def text_to_sequence(text, p=0.0):
if p >= 0:
text = mix_pronunciation(text, p)
from deepvoice3_pytorch.frontend.text import text_to_sequence
text = text_to_sequence(text, ["english_cleaners"])
return text
def text_to_sequence(text, p=0.0):
from deepvoice3_pytorch.frontend.text import text_to_sequence
text = text_to_sequence(text, ["estonian_cleaners"])
return text
def mix_pronunciation(text, p):
#text = '%'.join(word for word in text.split(', '))
text = ' '.join(_maybe_get_arpabet(word, p) for word in text.split(' '))
return text
def text_to_sequence(text, p=0.0):
text = normalize_numbers(text)
text = text.replace('\r', '')
text = text + '.' if text[-1] not in '!,.:;?' else text
if p >= 0:
text = mix_pronunciation(text, p)
from deepvoice3_pytorch.frontend.text import text_to_sequence
text = text_to_sequence(text, ["english_cleaners"])
return text
from deepvoice3_pytorch.frontend.text import sequence_to_text
#test
if __name__ == '__main__':
print('input ratio:')
p = float(input())
print('input English sentence:')
text = input()
seq = text_to_sequence(text, p)
print('sequence:{}'.format(seq))
seq2text = sequence_to_text(seq)
print('sequence to text:{}'.format(seq2text))
def text_to_sequence_original(text, p):
from deepvoice3_pytorch.frontend.text import text_to_sequence
text = text_to_sequence(text, ["french_cleaners"])
return text