Spaces:
Running
Running
# modified from https://github.com/CjangCjengh/vits/blob/main/text/japanese.py | |
import re | |
import pyopenjtalk | |
import os | |
import hashlib | |
from text.symbols2 import symbols | |
current_file_path = os.path.dirname(__file__) | |
def get_hash(fp: str) -> str: | |
hash_md5 = hashlib.md5() | |
with open(fp, "rb") as f: | |
for chunk in iter(lambda: f.read(4096), b""): | |
hash_md5.update(chunk) | |
return hash_md5.hexdigest() | |
USERDIC_CSV_PATH = os.path.join(current_file_path, "ja_userdic", "userdict.csv") | |
USERDIC_BIN_PATH = os.path.join(current_file_path, "ja_userdic", "user.dict") | |
USERDIC_HASH_PATH = os.path.join(current_file_path, "ja_userdic", "userdict.md5") | |
# 如果没有用户词典,就生成一个;如果有,就检查md5,如果不一样,就重新生成 | |
try: | |
if os.path.exists(USERDIC_BIN_PATH): | |
pyopenjtalk.update_global_jtalk_with_user_dict(USERDIC_BIN_PATH) | |
except: | |
print("FAIL TO USE USERDICT") | |
from text.symbols import punctuation | |
# Regular expression matching Japanese without punctuation marks: | |
_japanese_characters = re.compile( | |
r"[A-Za-z\d\u3005\u3040-\u30ff\u4e00-\u9fff\uff11-\uff19\uff21-\uff3a\uff41-\uff5a\uff66-\uff9d]" | |
) | |
# Regular expression matching non-Japanese characters or punctuation marks: | |
_japanese_marks = re.compile( | |
r"[^A-Za-z\d\u3005\u3040-\u30ff\u4e00-\u9fff\uff11-\uff19\uff21-\uff3a\uff41-\uff5a\uff66-\uff9d]" | |
) | |
# List of (symbol, Japanese) pairs for marks: | |
_symbols_to_japanese = [(re.compile("%s" % x[0]), x[1]) for x in [("%", "パーセント")]] | |
# List of (consonant, sokuon) pairs: | |
_real_sokuon = [ | |
(re.compile("%s" % x[0]), x[1]) | |
for x in [ | |
(r"Q([↑↓]*[kg])", r"k#\1"), | |
(r"Q([↑↓]*[tdjʧ])", r"t#\1"), | |
(r"Q([↑↓]*[sʃ])", r"s\1"), | |
(r"Q([↑↓]*[pb])", r"p#\1"), | |
] | |
] | |
# List of (consonant, hatsuon) pairs: | |
_real_hatsuon = [ | |
(re.compile("%s" % x[0]), x[1]) | |
for x in [ | |
(r"N([↑↓]*[pbm])", r"m\1"), | |
(r"N([↑↓]*[ʧʥj])", r"n^\1"), | |
(r"N([↑↓]*[tdn])", r"n\1"), | |
(r"N([↑↓]*[kg])", r"ŋ\1"), | |
] | |
] | |
def post_replace_ph(ph): | |
rep_map = { | |
":": ",", | |
";": ",", | |
",": ",", | |
"。": ".", | |
"!": "!", | |
"?": "?", | |
"\n": ".", | |
"·": ",", | |
"、": ",", | |
"...": "…", | |
} | |
if ph in rep_map.keys(): | |
ph = rep_map[ph] | |
if ph in symbols: | |
return ph | |
if ph not in symbols: | |
ph = "UNK" | |
return ph | |
def replace_consecutive_punctuation(text): | |
punctuations = ''.join(re.escape(p) for p in punctuation) | |
pattern = f'([{punctuations}])([{punctuations}])+' | |
result = re.sub(pattern, r'\1', text) | |
return result | |
def symbols_to_japanese(text): | |
for regex, replacement in _symbols_to_japanese: | |
text = re.sub(regex, replacement, text) | |
return text | |
def preprocess_jap(text, with_prosody=False): | |
"""Reference https://r9y9.github.io/ttslearn/latest/notebooks/ch10_Recipe-Tacotron.html""" | |
text = symbols_to_japanese(text) | |
sentences = re.split(_japanese_marks, text) | |
marks = re.findall(_japanese_marks, text) | |
text = [] | |
for i, sentence in enumerate(sentences): | |
if re.match(_japanese_characters, sentence): | |
if with_prosody: | |
text += pyopenjtalk_g2p_prosody(sentence)[1:-1] | |
else: | |
p = pyopenjtalk.g2p(sentence) | |
text += p.split(" ") | |
if i < len(marks): | |
if marks[i] == " ":# 防止意外的UNK | |
continue | |
text += [marks[i].replace(" ", "")] | |
return text | |
def text_normalize(text): | |
# todo: jap text normalize | |
# 避免重复标点引起的参考泄露 | |
text = replace_consecutive_punctuation(text) | |
text = "".join([i.lower() for i in text]) | |
return text | |
# Copied from espnet https://github.com/espnet/espnet/blob/master/espnet2/text/phoneme_tokenizer.py | |
def pyopenjtalk_g2p_prosody(text, drop_unvoiced_vowels=True): | |
"""Extract phoneme + prosoody symbol sequence from input full-context labels. | |
The algorithm is based on `Prosodic features control by symbols as input of | |
sequence-to-sequence acoustic modeling for neural TTS`_ with some r9y9's tweaks. | |
Args: | |
text (str): Input text. | |
drop_unvoiced_vowels (bool): whether to drop unvoiced vowels. | |
Returns: | |
List[str]: List of phoneme + prosody symbols. | |
Examples: | |
>>> from espnet2.text.phoneme_tokenizer import pyopenjtalk_g2p_prosody | |
>>> pyopenjtalk_g2p_prosody("こんにちは。") | |
['^', 'k', 'o', '[', 'N', 'n', 'i', 'ch', 'i', 'w', 'a', '$'] | |
.. _`Prosodic features control by symbols as input of sequence-to-sequence acoustic | |
modeling for neural TTS`: https://doi.org/10.1587/transinf.2020EDP7104 | |
""" | |
labels = pyopenjtalk.make_label(pyopenjtalk.run_frontend(text)) | |
N = len(labels) | |
phones = [] | |
for n in range(N): | |
lab_curr = labels[n] | |
# current phoneme | |
p3 = re.search(r"\-(.*?)\+", lab_curr).group(1) | |
# deal unvoiced vowels as normal vowels | |
if drop_unvoiced_vowels and p3 in "AEIOU": | |
p3 = p3.lower() | |
# deal with sil at the beginning and the end of text | |
if p3 == "sil": | |
assert n == 0 or n == N - 1 | |
if n == 0: | |
phones.append("^") | |
elif n == N - 1: | |
# check question form or not | |
e3 = _numeric_feature_by_regex(r"!(\d+)_", lab_curr) | |
if e3 == 0: | |
phones.append("$") | |
elif e3 == 1: | |
phones.append("?") | |
continue | |
elif p3 == "pau": | |
phones.append("_") | |
continue | |
else: | |
phones.append(p3) | |
# accent type and position info (forward or backward) | |
a1 = _numeric_feature_by_regex(r"/A:([0-9\-]+)\+", lab_curr) | |
a2 = _numeric_feature_by_regex(r"\+(\d+)\+", lab_curr) | |
a3 = _numeric_feature_by_regex(r"\+(\d+)/", lab_curr) | |
# number of mora in accent phrase | |
f1 = _numeric_feature_by_regex(r"/F:(\d+)_", lab_curr) | |
a2_next = _numeric_feature_by_regex(r"\+(\d+)\+", labels[n + 1]) | |
# accent phrase border | |
if a3 == 1 and a2_next == 1 and p3 in "aeiouAEIOUNcl": | |
phones.append("#") | |
# pitch falling | |
elif a1 == 0 and a2_next == a2 + 1 and a2 != f1: | |
phones.append("]") | |
# pitch rising | |
elif a2 == 1 and a2_next == 2: | |
phones.append("[") | |
return phones | |
# Copied from espnet https://github.com/espnet/espnet/blob/master/espnet2/text/phoneme_tokenizer.py | |
def _numeric_feature_by_regex(regex, s): | |
match = re.search(regex, s) | |
if match is None: | |
return -50 | |
return int(match.group(1)) | |
def g2p(norm_text, with_prosody=True): | |
norm_text = text_normalize(norm_text) | |
phones = preprocess_jap(norm_text, with_prosody) | |
phones = [post_replace_ph(i) for i in phones] | |
# todo: implement tones and word2ph | |
return phones | |
if __name__ == "__main__": | |
phones = g2p("こんにちは, hello, AKITOです,よろしくお願いしますね!") | |
print(phones) | |