coqui-tts/TTS/tts/layers/xtts/tokenizer.py

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import os
import re
import json
import torch
from tokenizers import Tokenizer
import pypinyin
from num2words import num2words
from TTS.tts.layers.xtts.zh_num2words import TextNorm as zh_num2words
_whitespace_re = re.compile(r"\s+")
# List of (regular expression, replacement) pairs for abbreviations:
_abbreviations = {
"en": [
(re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
for x in [
("mrs", "misess"),
("mr", "mister"),
("dr", "doctor"),
("st", "saint"),
("co", "company"),
("jr", "junior"),
("maj", "major"),
("gen", "general"),
("drs", "doctors"),
("rev", "reverend"),
("lt", "lieutenant"),
("hon", "honorable"),
("sgt", "sergeant"),
("capt", "captain"),
("esq", "esquire"),
("ltd", "limited"),
("col", "colonel"),
("ft", "fort"),
]
],
"es": [
(re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
for x in [
("sra", "señora"),
("sr", "señor"),
("dr", "doctor"),
("dra", "doctora"),
("st", "santo"),
("co", "compañía"),
("jr", "junior"),
("ltd", "limitada"),
]
],
"fr": [
(re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
for x in [
("mme", "madame"),
("mr", "monsieur"),
("dr", "docteur"),
("st", "saint"),
("co", "compagnie"),
("jr", "junior"),
("ltd", "limitée"),
]
],
"de": [
(re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
for x in [
("fr", "frau"),
("dr", "doktor"),
("st", "sankt"),
("co", "firma"),
("jr", "junior"),
]
],
"pt": [
(re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
for x in [
("sra", "senhora"),
("sr", "senhor"),
("dr", "doutor"),
("dra", "doutora"),
("st", "santo"),
("co", "companhia"),
("jr", "júnior"),
("ltd", "limitada"),
]
],
"it": [
(re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
for x in [
#("sig.ra", "signora"),
("sig", "signore"),
("dr", "dottore"),
("st", "santo"),
("co", "compagnia"),
("jr", "junior"),
("ltd", "limitata"),
]
],
"pl": [
(re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
for x in [
("p", "pani"),
("m", "pan"),
("dr", "doktor"),
("sw", "święty"),
("jr", "junior"),
]
],
"ar": [
(re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
for x in [
# There are not many common abbreviations in Arabic as in English.
]
],
"zh-cn": [
(re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
for x in [
# Chinese doesn't typically use abbreviations in the same way as Latin-based scripts.
]
],
"cs": [
(re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
for x in [
("dr", "doktor"), # doctor
("ing", "inženýr"), # engineer
("p", "pan"), # Could also map to pani for woman but no easy way to do it
# Other abbreviations would be specialized and not as common.
]
],
"ru": [
(re.compile("\\b%s\\b" % x[0], re.IGNORECASE), x[1])
for x in [
("г-жа", "госпожа"), # Mrs.
("г", "господин"), # Mr.
("д-р", "доктор"), # doctor
# Other abbreviations are less common or specialized.
]
],
"nl": [
(re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
for x in [
("dhr", "de heer"), # Mr.
("mevr", "mevrouw"), # Mrs.
("dr", "dokter"), # doctor
("jhr", "jonkheer"), # young lord or nobleman
# Dutch uses more abbreviations, but these are the most common ones.
]
],
"tr": [
(re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
for x in [
("b", "bay"), # Mr.
("byk", "büyük"), # büyük
("dr", "doktor"), # doctor
# Add other Turkish abbreviations here if needed.
]
],
}
def expand_abbreviations_multilingual(text, lang='en'):
for regex, replacement in _abbreviations[lang]:
text = re.sub(regex, replacement, text)
return text
_symbols_multilingual = {
'en': [
(re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
for x in [
("&", " and "),
("@", " at "),
("%", " percent "),
("#", " hash "),
("$", " dollar "),
("£", " pound "),
("°", " degree ")
]
],
'es': [
(re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
for x in [
("&", " y "),
("@", " arroba "),
("%", " por ciento "),
("#", " numeral "),
("$", " dolar "),
("£", " libra "),
("°", " grados ")
]
],
'fr': [
(re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
for x in [
("&", " et "),
("@", " arobase "),
("%", " pour cent "),
("#", " dièse "),
("$", " dollar "),
("£", " livre "),
("°", " degrés ")
]
],
'de': [
(re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
for x in [
("&", " und "),
("@", " at "),
("%", " prozent "),
("#", " raute "),
("$", " dollar "),
("£", " pfund "),
("°", " grad ")
]
],
'pt': [
(re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
for x in [
("&", " e "),
("@", " arroba "),
("%", " por cento "),
("#", " cardinal "),
("$", " dólar "),
("£", " libra "),
("°", " graus ")
]
],
'it': [
(re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
for x in [
("&", " e "),
("@", " chiocciola "),
("%", " per cento "),
("#", " cancelletto "),
("$", " dollaro "),
("£", " sterlina "),
("°", " gradi ")
]
],
'pl': [
(re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
for x in [
("&", " i "),
("@", " małpa "),
("%", " procent "),
("#", " krzyżyk "),
("$", " dolar "),
("£", " funt "),
("°", " stopnie ")
]
],
"ar": [
# Arabic
(re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
for x in [
("&", " و "),
("@", " على "),
("%", " في المئة "),
("#", " رقم "),
("$", " دولار "),
("£", " جنيه "),
("°", " درجة ")
]
],
"zh-cn": [
# Chinese
(re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
for x in [
("&", ""),
("@", ""),
("%", " 百分之 "),
("#", ""),
("$", " 美元 "),
("£", " 英镑 "),
("°", "")
]
],
"cs": [
# Czech
(re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
for x in [
("&", " a "),
("@", " na "),
("%", " procento "),
("#", " křížek "),
("$", " dolar "),
("£", " libra "),
("°", " stupně ")
]
],
"ru": [
# Russian
(re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
for x in [
("&", " и "),
("@", " собака "),
("%", " процентов "),
("#", " номер "),
("$", " доллар "),
("£", " фунт "),
("°", " градус ")
]
],
"nl": [
# Dutch
(re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
for x in [
("&", " en "),
("@", " bij "),
("%", " procent "),
("#", " hekje "),
("$", " dollar "),
("£", " pond "),
("°", " graden ")
]
],
"tr": [
(re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
for x in [
("&", " ve "),
("@", " at "),
("%", " yüzde "),
("#", " diyez "),
("$", " dolar "),
("£", " sterlin "),
("°", " derece ")
]
],
}
def expand_symbols_multilingual(text, lang='en'):
for regex, replacement in _symbols_multilingual[lang]:
text = re.sub(regex, replacement, text)
text = text.replace(' ', ' ') # Ensure there are no double spaces
return text.strip()
_ordinal_re = {
"en": re.compile(r"([0-9]+)(st|nd|rd|th)"),
"es": re.compile(r"([0-9]+)(º|ª|er|o|a|os|as)"),
"fr": re.compile(r"([0-9]+)(º|ª|er|re|e|ème)"),
"de": re.compile(r"([0-9]+)(st|nd|rd|th|º|ª|\.(?=\s|$))"),
"pt": re.compile(r"([0-9]+)(º|ª|o|a|os|as)"),
"it": re.compile(r"([0-9]+)(º|°|ª|o|a|i|e)"),
"pl": re.compile(r"([0-9]+)(º|ª|st|nd|rd|th)"),
"ar": re.compile(r"([0-9]+)(ون|ين|ث|ر|ى)"),
"cs": re.compile(r"([0-9]+)\.(?=\s|$)"), # In Czech, a dot is often used after the number to indicate ordinals.
"ru": re.compile(r"([0-9]+)(-й|-я|-е|-ое|-ье|-го)"),
"nl": re.compile(r"([0-9]+)(de|ste|e)"),
"tr": re.compile(r"([0-9]+)(\.|inci|nci|uncu|üncü|\.)"),
}
_number_re = re.compile(r"[0-9]+")
_currency_re = {
'USD': re.compile(r"((\$[0-9\.\,]*[0-9]+)|([0-9\.\,]*[0-9]+\$))"),
'GBP': re.compile(r"((£[0-9\.\,]*[0-9]+)|([0-9\.\,]*[0-9]+£))"),
'EUR': re.compile(r"(([0-9\.\,]*[0-9]+€)|((€[0-9\.\,]*[0-9]+)))")
}
_comma_number_re = re.compile(r"\b\d{1,3}(,\d{3})*(\.\d+)?\b")
_dot_number_re = re.compile(r"\b\d{1,3}(.\d{3})*(\,\d+)?\b")
_decimal_number_re = re.compile(r"([0-9]+[.,][0-9]+)")
def _remove_commas(m):
text = m.group(0)
if "," in text:
text = text.replace(",", "")
return text
def _remove_dots(m):
text = m.group(0)
if "." in text:
text = text.replace(".", "")
return text
def _expand_decimal_point(m, lang='en'):
amount = m.group(1).replace(",", ".")
return num2words(float(amount), lang=lang if lang != "cs" else "cz")
def _expand_currency(m, lang='en', currency='USD'):
amount = float((re.sub(r'[^\d.]', '', m.group(0).replace(",", "."))))
full_amount = num2words(amount, to='currency', currency=currency, lang=lang if lang != "cs" else "cz")
and_equivalents = {
"en": ", ",
"es": " con ",
"fr": " et ",
"de": " und ",
"pt": " e ",
"it": " e ",
"pl": ", ",
"cs": ", ",
"ru": ", ",
"nl": ", ",
"ar": ", ",
"tr": ", ",
}
if amount.is_integer():
last_and = full_amount.rfind(and_equivalents[lang])
if last_and != -1:
full_amount = full_amount[:last_and]
return full_amount
def _expand_ordinal(m, lang='en'):
return num2words(int(m.group(1)), ordinal=True, lang=lang if lang != "cs" else "cz")
def _expand_number(m, lang='en'):
return num2words(int(m.group(0)), lang=lang if lang != "cs" else "cz")
def expand_numbers_multilingual(text, lang='en'):
if lang == "zh-cn":
text = zh_num2words()(text)
else:
if lang in ["en", "ru"]:
text = re.sub(_comma_number_re, _remove_commas, text)
else:
text = re.sub(_dot_number_re, _remove_dots, text)
try:
text = re.sub(_currency_re['GBP'], lambda m: _expand_currency(m, lang, 'GBP'), text)
text = re.sub(_currency_re['USD'], lambda m: _expand_currency(m, lang, 'USD'), text)
text = re.sub(_currency_re['EUR'], lambda m: _expand_currency(m, lang, 'EUR'), text)
except:
pass
if lang != "tr":
text = re.sub(_decimal_number_re, lambda m: _expand_decimal_point(m, lang), text)
text = re.sub(_ordinal_re[lang], lambda m: _expand_ordinal(m, lang), text)
text = re.sub(_number_re, lambda m: _expand_number(m, lang), text)
return text
def lowercase(text):
return text.lower()
def collapse_whitespace(text):
return re.sub(_whitespace_re, " ", text)
def multilingual_cleaners(text, lang):
text = text.replace('"', '')
if lang=="tr":
text = text.replace("İ", "i")
text = text.replace("Ö", "ö")
text = text.replace("Ü", "ü")
text = lowercase(text)
text = expand_numbers_multilingual(text, lang)
text = expand_abbreviations_multilingual(text, lang)
text = expand_symbols_multilingual(text, lang=lang)
text = collapse_whitespace(text)
return text
def basic_cleaners(text):
"""Basic pipeline that lowercases and collapses whitespace without transliteration."""
text = lowercase(text)
text = collapse_whitespace(text)
return text
def chinese_transliterate(text):
return "".join([p[0] for p in pypinyin.pinyin(text, style=pypinyin.Style.TONE3, heteronym=False, neutral_tone_with_five=True)])
def japanese_cleaners(text, katsu):
text = katsu.romaji(text)
text = lowercase(text)
return text
class VoiceBpeTokenizer:
def __init__(self, vocab_file=None, preprocess=None):
self.tokenizer = None
self.katsu = None
if vocab_file is not None:
with open(vocab_file, "r", encoding="utf-8") as f:
vocab = json.load(f)
self.language = vocab["model"]["language"] if "language" in vocab["model"] else None
if preprocess is None:
self.preprocess = "pre_tokenizer" in vocab and vocab["pre_tokenizer"]
else:
self.preprocess = preprocess
self.tokenizer = Tokenizer.from_file(vocab_file)
def preprocess_text(self, txt, lang):
if lang in ["en", "es", "fr", "de", "pt", "it", "pl", "ar", "cs", "ru", "nl", "tr", "zh-cn"]:
txt = multilingual_cleaners(txt, lang)
if lang == "zh-cn":
txt = chinese_transliterate(txt)
elif lang == "ja":
if self.katsu is None:
import cutlet
self.katsu = cutlet.Cutlet()
txt = japanese_cleaners(txt, self.katsu)
else:
raise NotImplementedError()
return txt
def encode(self, txt, lang):
if self.preprocess:
txt = self.preprocess_text(txt, lang)
txt = f"[{lang}]{txt}"
txt = txt.replace(" ", "[SPACE]")
return self.tokenizer.encode(txt).ids
def decode(self, seq):
if isinstance(seq, torch.Tensor):
seq = seq.cpu().numpy()
txt = self.tokenizer.decode(seq, skip_special_tokens=False).replace(" ", "")
txt = txt.replace("[SPACE]", " ")
txt = txt.replace("[STOP]", "")
txt = txt.replace("[UNK]", "")
return txt
def __len__(self):
return self.tokenizer.get_vocab_size()
def get_number_tokens(self):
return max(self.tokenizer.get_vocab().values()) + 1