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