5de4884075
pyopenjtalk_worker.initialize() has the side effect of starting another process and should not be executed automatically on import.
415 lines
11 KiB
Python
415 lines
11 KiB
Python
import pickle
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import os
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import re
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from pathlib import Path
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import inflect
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from g2p_en import G2p
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from style_bert_vits2.constants import Languages
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from style_bert_vits2.nlp import bert_models
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from style_bert_vits2.nlp.symbols import PUNCTUATIONS, SYMBOLS
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CMU_DICT_PATH = Path(__file__).parent / "cmudict.rep"
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CACHE_PATH = Path(__file__).parent / "cmudict_cache.pickle"
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def g2p(text: str) -> tuple[list[str], list[int], list[int]]:
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ARPA = {
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"AH0",
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"S",
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"AH1",
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"EY2",
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"AE2",
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"EH0",
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"OW2",
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"UH0",
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"NG",
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"B",
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"G",
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"AY0",
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"M",
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"AA0",
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"F",
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"AO0",
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"ER2",
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"UH1",
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"IY1",
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"AH2",
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"DH",
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"IY0",
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"EY1",
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"IH0",
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"K",
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"N",
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"W",
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"IY2",
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"T",
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"AA1",
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"ER1",
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"EH2",
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"OY0",
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"UH2",
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"UW1",
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"Z",
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"AW2",
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"AW1",
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"V",
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"UW2",
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"AA2",
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"ER",
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"AW0",
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"UW0",
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"R",
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"OW1",
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"EH1",
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"ZH",
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"AE0",
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"IH2",
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"IH",
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"Y",
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"JH",
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"P",
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"AY1",
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"EY0",
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"OY2",
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"TH",
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"HH",
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"D",
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"ER0",
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"CH",
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"AO1",
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"AE1",
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"AO2",
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"OY1",
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"AY2",
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"IH1",
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"OW0",
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"L",
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"SH",
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}
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_g2p = G2p()
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phones = []
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tones = []
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phone_len = []
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# tokens = [tokenizer.tokenize(i) for i in words]
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words = __text_to_words(text)
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eng_dict = __get_dict()
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for word in words:
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temp_phones, temp_tones = [], []
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if len(word) > 1:
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if "'" in word:
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word = ["".join(word)]
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for w in word:
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if w in PUNCTUATIONS:
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temp_phones.append(w)
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temp_tones.append(0)
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continue
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if w.upper() in eng_dict:
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phns, tns = __refine_syllables(eng_dict[w.upper()])
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temp_phones += [__post_replace_ph(i) for i in phns]
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temp_tones += tns
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# w2ph.append(len(phns))
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else:
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phone_list = list(filter(lambda p: p != " ", _g2p(w))) # type: ignore
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phns = []
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tns = []
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for ph in phone_list:
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if ph in ARPA:
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ph, tn = __refine_ph(ph)
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phns.append(ph)
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tns.append(tn)
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else:
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phns.append(ph)
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tns.append(0)
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temp_phones += [__post_replace_ph(i) for i in phns]
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temp_tones += tns
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phones += temp_phones
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tones += temp_tones
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phone_len.append(len(temp_phones))
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# phones = [post_replace_ph(i) for i in phones]
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word2ph = []
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for token, pl in zip(words, phone_len):
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word_len = len(token)
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aaa = __distribute_phone(pl, word_len)
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word2ph += aaa
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phones = ["_"] + phones + ["_"]
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tones = [0] + tones + [0]
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word2ph = [1] + word2ph + [1]
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assert len(phones) == len(tones), text
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assert len(phones) == sum(word2ph), text
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return phones, tones, word2ph
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def normalize_text(text: str) -> str:
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text = __normalize_numbers(text)
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text = __replace_punctuation(text)
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text = re.sub(r"([,;.\?\!])([\w])", r"\1 \2", text)
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return text
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def __normalize_numbers(text: str) -> str:
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text = re.sub(__comma_number_re, __remove_commas, text)
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text = re.sub(__pounds_re, r"\1 pounds", text)
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text = re.sub(__dollars_re, __expand_dollars, text)
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text = re.sub(__decimal_number_re, __expand_decimal_point, text)
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text = re.sub(__ordinal_re, __expand_ordinal, text)
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text = re.sub(__number_re, __expand_number, text)
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return text
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def __replace_punctuation(text: str) -> str:
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REPLACE_MAP = {
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"：": ",",
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"；": ",",
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"，": ",",
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"。": ".",
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"！": "!",
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"？": "?",
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"\n": ".",
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"．": ".",
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"…": "...",
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"···": "...",
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"・・・": "...",
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"·": ",",
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"・": ",",
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"、": ",",
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"$": ".",
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"“": "'",
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"”": "'",
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'"': "'",
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"‘": "'",
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"’": "'",
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"（": "'",
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"）": "'",
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"(": "'",
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")": "'",
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"《": "'",
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"》": "'",
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"【": "'",
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"】": "'",
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"[": "'",
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"]": "'",
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"—": "-",
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"−": "-",
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"～": "-",
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"~": "-",
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"「": "'",
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"」": "'",
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}
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pattern = re.compile("|".join(re.escape(p) for p in REPLACE_MAP.keys()))
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replaced_text = pattern.sub(lambda x: REPLACE_MAP[x.group()], text)
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# replaced_text = re.sub(
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# r"[^\u3040-\u309F\u30A0-\u30FF\u4E00-\u9FFF\u3400-\u4DBF\u3005"
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# + "".join(punctuation)
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# + r"]+",
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# "",
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# replaced_text,
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# )
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return replaced_text
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def __post_replace_ph(ph: str) -> str:
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REPLACE_MAP = {
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"：": ",",
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"；": ",",
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"，": ",",
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"。": ".",
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"！": "!",
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"？": "?",
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"\n": ".",
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"·": ",",
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"、": ",",
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"…": "...",
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"···": "...",
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"・・・": "...",
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"v": "V",
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}
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if ph in REPLACE_MAP.keys():
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ph = REPLACE_MAP[ph]
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if ph in SYMBOLS:
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return ph
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if ph not in SYMBOLS:
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ph = "UNK"
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return ph
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def __read_dict() -> dict[str, list[list[str]]]:
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g2p_dict = {}
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start_line = 49
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with open(CMU_DICT_PATH) as f:
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line = f.readline()
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line_index = 1
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while line:
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if line_index >= start_line:
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line = line.strip()
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word_split = line.split(" ")
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word = word_split[0]
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syllable_split = word_split[1].split(" - ")
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g2p_dict[word] = []
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for syllable in syllable_split:
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phone_split = syllable.split(" ")
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g2p_dict[word].append(phone_split)
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line_index = line_index + 1
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line = f.readline()
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return g2p_dict
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def __cache_dict(g2p_dict: dict[str, list[list[str]]], file_path: Path) -> None:
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with open(file_path, "wb") as pickle_file:
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pickle.dump(g2p_dict, pickle_file)
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def __get_dict() -> dict[str, list[list[str]]]:
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if CACHE_PATH.exists():
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with open(CACHE_PATH, "rb") as pickle_file:
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g2p_dict = pickle.load(pickle_file)
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else:
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g2p_dict = __read_dict()
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__cache_dict(g2p_dict, CACHE_PATH)
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return g2p_dict
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def __refine_ph(phn: str) -> tuple[str, int]:
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tone = 0
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if re.search(r"\d$", phn):
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tone = int(phn[-1]) + 1
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phn = phn[:-1]
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else:
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tone = 3
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return phn.lower(), tone
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def __refine_syllables(syllables: list[list[str]]) -> tuple[list[str], list[int]]:
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tones = []
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phonemes = []
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for phn_list in syllables:
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for i in range(len(phn_list)):
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phn = phn_list[i]
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phn, tone = __refine_ph(phn)
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phonemes.append(phn)
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tones.append(tone)
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return phonemes, tones
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__inflect = inflect.engine()
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__comma_number_re = re.compile(r"([0-9][0-9\,]+[0-9])")
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__decimal_number_re = re.compile(r"([0-9]+\.[0-9]+)")
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__pounds_re = re.compile(r"£([0-9\,]*[0-9]+)")
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__dollars_re = re.compile(r"\$([0-9\.\,]*[0-9]+)")
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__ordinal_re = re.compile(r"[0-9]+(st|nd|rd|th)")
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__number_re = re.compile(r"[0-9]+")
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def __expand_dollars(m: re.Match[str]) -> str:
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match = m.group(1)
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parts = match.split(".")
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if len(parts) > 2:
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return match + " dollars" # Unexpected format
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dollars = int(parts[0]) if parts[0] else 0
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cents = int(parts[1]) if len(parts) > 1 and parts[1] else 0
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if dollars and cents:
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dollar_unit = "dollar" if dollars == 1 else "dollars"
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cent_unit = "cent" if cents == 1 else "cents"
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return "%s %s, %s %s" % (dollars, dollar_unit, cents, cent_unit)
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elif dollars:
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dollar_unit = "dollar" if dollars == 1 else "dollars"
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return "%s %s" % (dollars, dollar_unit)
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elif cents:
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cent_unit = "cent" if cents == 1 else "cents"
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return "%s %s" % (cents, cent_unit)
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else:
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return "zero dollars"
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def __remove_commas(m: re.Match[str]) -> str:
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return m.group(1).replace(",", "")
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def __expand_ordinal(m: re.Match[str]) -> str:
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return __inflect.number_to_words(m.group(0)) # type: ignore
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def __expand_number(m: re.Match[str]) -> str:
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num = int(m.group(0))
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if num > 1000 and num < 3000:
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if num == 2000:
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return "two thousand"
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elif num > 2000 and num < 2010:
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return "two thousand " + __inflect.number_to_words(num % 100) # type: ignore
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elif num % 100 == 0:
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return __inflect.number_to_words(num // 100) + " hundred" # type: ignore
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else:
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return __inflect.number_to_words(
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num, andword="", zero="oh", group=2 # type: ignore
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).replace(", ", " ") # type: ignore
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else:
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return __inflect.number_to_words(num, andword="") # type: ignore
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def __expand_decimal_point(m: re.Match[str]) -> str:
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return m.group(1).replace(".", " point ")
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def __distribute_phone(n_phone: int, n_word: int) -> list[int]:
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phones_per_word = [0] * n_word
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for task in range(n_phone):
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min_tasks = min(phones_per_word)
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min_index = phones_per_word.index(min_tasks)
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phones_per_word[min_index] += 1
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return phones_per_word
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def __text_to_words(text: str) -> list[list[str]]:
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tokenizer = bert_models.load_tokenizer(Languages.EN)
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tokens = tokenizer.tokenize(text)
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words = []
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for idx, t in enumerate(tokens):
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if t.startswith("▁"):
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words.append([t[1:]])
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else:
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if t in PUNCTUATIONS:
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if idx == len(tokens) - 1:
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words.append([f"{t}"])
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else:
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if (
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not tokens[idx + 1].startswith("▁")
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and tokens[idx + 1] not in PUNCTUATIONS
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):
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if idx == 0:
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words.append([])
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words[-1].append(f"{t}")
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else:
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words.append([f"{t}"])
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else:
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if idx == 0:
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words.append([])
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words[-1].append(f"{t}")
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return words
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if __name__ == "__main__":
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# print(get_dict())
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# print(eng_word_to_phoneme("hello"))
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print(g2p("In this paper, we propose 1 DSPGAN, a GAN-based universal vocoder."))
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# all_phones = set()
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# eng_dict = get_dict()
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# for k, syllables in eng_dict.items():
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# for group in syllables:
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# for ph in group:
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# all_phones.add(ph)
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# print(all_phones)
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