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| # modified from https://github.com/CjangCjengh/vits/blob/main/text/japanese.py | |
| import re | |
| import sys | |
| import pyopenjtalk | |
| from text import symbols | |
| # 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 [("οΌ ", "γγΌγ»γ³γ")]] | |
| # List of (consonant, sokuon) pairs: | |
| _real_sokuon = [ | |
| (re.compile("%s" % x[0]), x[1]) | |
| for x in [ | |
| (r"Q([ββ]*[kg])", r"k#\1"), | |
| (r"Q([ββ]*[tdjΚ§])", r"t#\1"), | |
| (r"Q([ββ]*[sΚ])", r"s\1"), | |
| (r"Q([ββ]*[pb])", r"p#\1"), | |
| ] | |
| ] | |
| # List of (consonant, hatsuon) pairs: | |
| _real_hatsuon = [ | |
| (re.compile("%s" % x[0]), x[1]) | |
| for x in [ | |
| (r"N([ββ]*[pbm])", r"m\1"), | |
| (r"N([ββ]*[Κ§Κ₯j])", r"n^\1"), | |
| (r"N([ββ]*[tdn])", r"n\1"), | |
| (r"N([ββ]*[kg])", r"Ε\1"), | |
| ] | |
| ] | |
| def post_replace_ph(ph): | |
| rep_map = { | |
| "οΌ": ",", | |
| "οΌ": ",", | |
| "οΌ": ",", | |
| "γ": ".", | |
| "οΌ": "!", | |
| "οΌ": "?", | |
| "\n": ".", | |
| "Β·": ",", | |
| "γ": ",", | |
| "...": "β¦", | |
| } | |
| 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 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] == " ":# ι²ζ’ζε€ηUNK | |
| continue | |
| text += [marks[i].replace(" ", "")] | |
| return text | |
| def text_normalize(text): | |
| # todo: jap text normalize | |
| 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("γγγ«γ‘γ―γ") | |
| ['^', '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=False): | |
| 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("γγγ«γ‘γ―, hello, AKITOγ§γ,γγγγγι‘γγγΎγγοΌ") | |
| print(phones) |