artificial-styletts2 / text_utils.py
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# -*- coding: utf-8 -*-
import numpy as np
import re
import codecs
# IPA Phonemizer: https://github.com/bootphon/phonemizer
_pad = "$"
_punctuation = ';:,.!?¡¿—…"«»“” '
_letters = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz'
_letters_ipa = "ɑɐɒæɓʙβɔɕçɗɖðʤəɘɚɛɜɝɞɟʄɡɠɢʛɦɧħɥʜɨɪʝɭɬɫɮʟɱɯɰŋɳɲɴøɵɸθœɶʘɹɺɾɻʀʁɽʂʃʈʧʉʊʋⱱʌɣɤʍχʎʏʑʐʒʔʡʕʢǀǁǂǃˈˌːˑʼʴʰʱʲʷˠˤ˞↓↑→↗↘'̩'ᵻ"
# Export all symbols:
symbols = [_pad] + list(_punctuation) + list(_letters) + list(_letters_ipa)
dicts = {}
for i in range(len((symbols))):
dicts[symbols[i]] = i
class TextCleaner:
def __init__(self, dummy=None):
self.word_index_dictionary = dicts
print(len(dicts))
def __call__(self, text):
indexes = []
for char in text:
try:
indexes.append(self.word_index_dictionary[char])
except KeyError:
print(text)
return indexes
# == Sentence Splitter
alphabets= "([A-Za-z])"
prefixes = "(Mr|St|Mrs|Ms|Dr)[.]"
suffixes = "(Inc|Ltd|Jr|Sr|Co)"
starters = "(Mr|Mrs|Ms|Dr|Prof|Capt|Cpt|Lt|He\s|She\s|It\s|They\s|Their\s|Our\s|We\s|But\s|However\s|That\s|This\s|Wherever)"
acronyms = "([A-Z][.][A-Z][.](?:[A-Z][.])?)"
websites = "[.](com|net|org|io|gov|edu|me)"
digits = "([0-9])"
multiple_dots = r'\.{2,}'
def split_into_sentences(text):
"""
Split the text into sentences.
If the text contains substrings "<prd>" or "<stop>", they would lead
to incorrect splitting because they are used as markers for splitting.
:param text: text to be split into sentences
:type text: str
:return: list of sentences
:rtype: list[str]
https://stackoverflow.com/questions/4576077/how-can-i-split-a-text-into-sentences
"""
text = " " + text + " "
text = text.replace("\n"," ")
text = re.sub(prefixes,"\\1<prd>",text)
text = re.sub(websites,"<prd>\\1",text)
text = re.sub(digits + "[.]" + digits,"\\1<prd>\\2",text)
text = re.sub(multiple_dots, lambda match: "<prd>" * len(match.group(0)) + "<stop>", text)
if "Ph.D" in text: text = text.replace("Ph.D.","Ph<prd>D<prd>")
text = re.sub("\s" + alphabets + "[.] "," \\1<prd> ",text)
text = re.sub(acronyms+" "+starters,"\\1<stop> \\2",text)
text = re.sub(alphabets + "[.]" + alphabets + "[.]" + alphabets + "[.]","\\1<prd>\\2<prd>\\3<prd>",text)
text = re.sub(alphabets + "[.]" + alphabets + "[.]","\\1<prd>\\2<prd>",text)
text = re.sub(" "+suffixes+"[.] "+starters," \\1<stop> \\2",text)
text = re.sub(" "+suffixes+"[.]"," \\1<prd>",text)
text = re.sub(" " + alphabets + "[.]"," \\1<prd>",text)
if "”" in text: text = text.replace(".”","”.")
if "\"" in text: text = text.replace(".\"","\".")
if "!" in text: text = text.replace("!\"","\"!")
if "?" in text: text = text.replace("?\"","\"?")
text = text.replace(".",".<stop>")
text = text.replace("?","?<stop>")
text = text.replace("!","!<stop>")
text = text.replace("<prd>",".")
sentences = text.split("<stop>")
sentences = [s.strip() for s in sentences]
if sentences and not sentences[-1]: sentences = sentences[:-1]
return sentences
def store_ssml(text=None,
voice=None):
'''create ssml:
text : list of sentences
voice: https://github.com/MycroftAI/mimic3-voices
'''
print('\n___________________________\n', len(text), text[0], '\n___________________________________\n')
_s = '<speak>'
for short_text in text:
rate = min(max(.87, len(short_text) / 76), 1.14) #1.44) # 1.24 for bieber
volume = int(74 * np.random.rand() + 24)
# text = ('<speak>'
_s += f'<prosody volume=\'{volume}\'>' # THe other voice does not have volume
_s += f'<prosody rate=\'{rate}\'>'
_s += f'<voice name=\'{voice}\'>'
_s += '<s>'
_s += short_text
_s += '</s>'
_s += '</voice>'
_s += '</prosody>'
_s += '</prosody>'
_s += '</speak>'
print(len(text),'\n\n\n\n\n\n\n', _s)
with codecs.open('_tmp_ssml.txt', 'w', "utf-8-sig") as f:
f.write(_s)