Spaces:
Sleeping
Sleeping
File size: 6,529 Bytes
ea6a7ed |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 |
"""adapted from https://github.com/keithito/tacotron"""
import re
import numpy as np
from .cleaners import Cleaner
from .symbols import get_symbols
from .grapheme_dictionary import Grapheme2PhonemeDictionary
#########
# REGEX #
#########
# Regular expression matching text enclosed in curly braces for encoding
_curly_re = re.compile(r"(.*?)\{(.+?)\}(.*)")
# Regular expression matching words and not words
_words_re = re.compile(
r"([a-zA-ZÀ-ž]+['][a-zA-ZÀ-ž]+|[a-zA-ZÀ-ž]+)|([{][^}]+[}]|[^a-zA-ZÀ-ž{}]+)"
)
def lines_to_list(filename):
with open(filename, encoding="utf-8") as f:
lines = f.readlines()
lines = [l.rstrip() for l in lines]
return lines
class TextProcessing(object):
def __init__(
self,
symbol_set,
cleaner_name,
heteronyms_path,
phoneme_dict_path,
p_phoneme,
handle_phoneme,
handle_phoneme_ambiguous,
prepend_space_to_text=False,
append_space_to_text=False,
add_bos_eos_to_text=False,
encoding="latin-1",
):
if heteronyms_path is not None and heteronyms_path != "":
self.heteronyms = set(lines_to_list(heteronyms_path))
else:
self.heteronyms = []
# phoneme dict
self.phonemedict = {}
self.p_phoneme = p_phoneme
self.handle_phoneme = handle_phoneme
self.handle_phoneme_ambiguous = handle_phoneme_ambiguous
self.symbols = get_symbols(symbol_set)
self.cleaner_names = cleaner_name
self.cleaner = Cleaner(cleaner_name, self.phonemedict)
self.prepend_space_to_text = prepend_space_to_text
self.append_space_to_text = append_space_to_text
self.add_bos_eos_to_text = add_bos_eos_to_text
if add_bos_eos_to_text:
self.symbols.append("<bos>")
self.symbols.append("<eos>")
# Mappings from symbol to numeric ID and vice versa:
self.symbol_to_id = {s: i for i, s in enumerate(self.symbols)}
self.id_to_symbol = {i: s for i, s in enumerate(self.symbols)}
def text_to_sequence(self, text):
sequence = []
# Check for curly braces and treat their contents as phoneme:
while len(text):
m = _curly_re.match(text)
if not m:
sequence += self.symbols_to_sequence(text)
break
sequence += self.symbols_to_sequence(m.group(1))
sequence += self.phoneme_to_sequence(m.group(2))
text = m.group(3)
return sequence
def sequence_to_text(self, sequence):
result = ""
for symbol_id in sequence:
if symbol_id in self.id_to_symbol:
s = self.id_to_symbol[symbol_id]
# Enclose phoneme back in curly braces:
if len(s) > 1 and s[0] == "@":
s = "{%s}" % s[1:]
result += s
return result.replace("}{", " ")
def clean_text(self, text):
text = self.cleaner(text)
return text
def symbols_to_sequence(self, symbols):
return [self.symbol_to_id[s] for s in symbols if s in self.symbol_to_id]
def phoneme_to_sequence(self, text):
return self.symbols_to_sequence(["@" + s for s in text.split()])
def get_phoneme(self, word):
phoneme_suffix = ""
if word.lower() in self.heteronyms:
return word
if len(word) > 2 and word.endswith("'s"):
phoneme = self.phonemedict.lookup(word)
if phoneme is None:
phoneme = self.phonemedict.lookup(word[:-2])
phoneme_suffix = "" if phoneme is None else " Z"
elif len(word) > 1 and word.endswith("s"):
phoneme = self.phonemedict.lookup(word)
if phoneme is None:
phoneme = self.phonemedict.lookup(word[:-1])
phoneme_suffix = "" if phoneme is None else " Z"
else:
phoneme = self.phonemedict.lookup(word)
if phoneme is None:
return word
if len(phoneme) > 1:
if self.handle_phoneme_ambiguous == "first":
phoneme = phoneme[0]
elif self.handle_phoneme_ambiguous == "random":
phoneme = np.random.choice(phoneme)
elif self.handle_phoneme_ambiguous == "ignore":
return word
else:
phoneme = phoneme[0]
phoneme = "{" + phoneme + phoneme_suffix + "}"
return phoneme
def encode_text(self, text, return_all=False):
text_clean = self.clean_text(text)
text = text_clean
text_phoneme = ""
if self.p_phoneme > 0:
text_phoneme = self.convert_to_phoneme(text)
text = text_phoneme
text_encoded = self.text_to_sequence(text)
if self.prepend_space_to_text:
text_encoded.insert(0, self.symbol_to_id[" "])
if self.append_space_to_text:
text_encoded.append(self.symbol_to_id[" "])
if self.add_bos_eos_to_text:
text_encoded.insert(0, self.symbol_to_id["<bos>"])
text_encoded.append(self.symbol_to_id["<eos>"])
if return_all:
return text_encoded, text_clean, text_phoneme
return text_encoded
def convert_to_phoneme(self, text):
if self.handle_phoneme == "sentence":
if np.random.uniform() < self.p_phoneme:
words = _words_re.findall(text)
text_phoneme = [
self.get_phoneme(word[0])
if (word[0] != "")
else re.sub(r"\s(\d)", r"\1", word[1].upper())
for word in words
]
text_phoneme = "".join(text_phoneme)
text = text_phoneme
elif self.handle_phoneme == "word":
words = _words_re.findall(text)
text_phoneme = [
re.sub(r"\s(\d)", r"\1", word[1].upper())
if word[0] == ""
else (
self.get_phoneme(word[0])
if np.random.uniform() < self.p_phoneme
else word[0]
)
for word in words
]
text_phoneme = "".join(text_phoneme)
text = text_phoneme
elif self.handle_phoneme != "":
raise Exception(
"{} handle_phoneme is not supported".format(self.handle_phoneme)
)
return text
|