import pickle import os import re from g2p_en import G2p from transformers import DebertaV2Tokenizer from text import symbols current_file_path = os.path.dirname(__file__) CMU_DICT_PATH = os.path.join(current_file_path, "cmudict.rep") CACHE_PATH = os.path.join(current_file_path, "cmudict_cache.pickle") _g2p = G2p() LOCAL_PATH = "./bert/deberta-v3-large" #LOCAL_PATH = 'microsoft/deberta-v3-large' tokenizer = DebertaV2Tokenizer.from_pretrained(LOCAL_PATH) 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", } def post_replace_ph(ph): rep_map = { ":": ",", ";": ",", ",": ",", "。": ".", "!": "!", "?": "?", "\n": ".", "·": ",", "、": ",", "…": "...", "···": "...", "・・・": "...", "v": "V", } 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 rep_map = { ":": ",", ";": ",", ",": ",", "。": ".", "!": "!", "?": "?", "\n": ".", ".": ".", "…": "...", "···": "...", "・・・": "...", "·": ",", "・": ",", "、": ",", "$": ".", "“": "'", "”": "'", '"': "'", "‘": "'", "’": "'", "(": "'", ")": "'", "(": "'", ")": "'", "《": "'", "》": "'", "【": "'", "】": "'", "[": "'", "]": "'", "—": "-", "−": "-", "~": "-", "~": "-", "「": "'", "」": "'", } def replace_punctuation(text): pattern = re.compile("|".join(re.escape(p) for p in rep_map.keys())) replaced_text = pattern.sub(lambda x: rep_map[x.group()], text) # replaced_text = re.sub( # r"[^\u3040-\u309F\u30A0-\u30FF\u4E00-\u9FFF\u3400-\u4DBF\u3005" # + "".join(punctuation) # + r"]+", # "", # replaced_text, # ) return replaced_text def read_dict(): g2p_dict = {} start_line = 49 with open(CMU_DICT_PATH) as f: line = f.readline() line_index = 1 while line: if line_index >= start_line: line = line.strip() word_split = line.split(" ") word = word_split[0] syllable_split = word_split[1].split(" - ") g2p_dict[word] = [] for syllable in syllable_split: phone_split = syllable.split(" ") g2p_dict[word].append(phone_split) line_index = line_index + 1 line = f.readline() return g2p_dict def cache_dict(g2p_dict, file_path): with open(file_path, "wb") as pickle_file: pickle.dump(g2p_dict, pickle_file) def get_dict(): if os.path.exists(CACHE_PATH): with open(CACHE_PATH, "rb") as pickle_file: g2p_dict = pickle.load(pickle_file) else: g2p_dict = read_dict() cache_dict(g2p_dict, CACHE_PATH) return g2p_dict eng_dict = get_dict() def refine_ph(phn): tone = 0 if re.search(r"\d$", phn): tone = int(phn[-1]) + 1 phn = phn[:-1] return phn.lower(), tone def refine_syllables(syllables): 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 import re import inflect _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]+") # List of (regular expression, replacement) pairs for abbreviations: _abbreviations = [ (re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1]) for x in [ ("mrs", "misess"), ("mr", "mister"), ("dr", "doctor"), ("st", "saint"), ("co", "company"), ("jr", "junior"), ("maj", "major"), ("gen", "general"), ("drs", "doctors"), ("rev", "reverend"), ("lt", "lieutenant"), ("hon", "honorable"), ("sgt", "sergeant"), ("capt", "captain"), ("esq", "esquire"), ("ltd", "limited"), ("col", "colonel"), ("ft", "fort"), ] ] # List of (ipa, lazy ipa) pairs: _lazy_ipa = [ (re.compile("%s" % x[0]), x[1]) for x in [ ("r", "ɹ"), ("æ", "e"), ("ɑ", "a"), ("ɔ", "o"), ("ð", "z"), ("θ", "s"), ("ɛ", "e"), ("ɪ", "i"), ("ʊ", "u"), ("ʒ", "ʥ"), ("ʤ", "ʥ"), ("ˈ", "↓"), ] ] # List of (ipa, lazy ipa2) pairs: _lazy_ipa2 = [ (re.compile("%s" % x[0]), x[1]) for x in [ ("r", "ɹ"), ("ð", "z"), ("θ", "s"), ("ʒ", "ʑ"), ("ʤ", "dʑ"), ("ˈ", "↓"), ] ] # List of (ipa, ipa2) pairs _ipa_to_ipa2 = [ (re.compile("%s" % x[0]), x[1]) for x in [("r", "ɹ"), ("ʤ", "dʒ"), ("ʧ", "tʃ")] ] def _expand_dollars(m): 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): return m.group(1).replace(",", "") def _expand_ordinal(m): return _inflect.number_to_words(m.group(0)) def _expand_number(m): 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) elif num % 100 == 0: return _inflect.number_to_words(num // 100) + " hundred" else: return _inflect.number_to_words( num, andword="", zero="oh", group=2 ).replace(", ", " ") else: return _inflect.number_to_words(num, andword="") def _expand_decimal_point(m): return m.group(1).replace(".", " point ") def normalize_numbers(text): 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 text_normalize(text): text = normalize_numbers(text) text = replace_punctuation(text) text = re.sub(r"([,;.\?\!])([\w])", r"\1 \2", text) return text def distribute_phone(n_phone, n_word): 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 sep_text(text): words = re.split(r"([,;.\?\!\s+])", text) words = [word for word in words if word.strip() != ""] return words def g2p(text): phones = [] tones = [] # word2ph = [] words = sep_text(text) tokens = [tokenizer.tokenize(i) for i in words] for word in words: if word.upper() in eng_dict: phns, tns = refine_syllables(eng_dict[word.upper()]) phones.append([post_replace_ph(i) for i in phns]) tones.append(tns) # word2ph.append(len(phns)) else: phone_list = list(filter(lambda p: p != " ", _g2p(word))) 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) phones.append([post_replace_ph(i) for i in phns]) tones.append(tns) # word2ph.append(len(phns)) # phones = [post_replace_ph(i) for i in phones] word2ph = [] for token, phoneme in zip(tokens, phones): phone_len = len(phoneme) word_len = len(token) aaa = distribute_phone(phone_len, word_len) word2ph += aaa phones = ["_"] + [j for i in phones for j in i] + ["_"] tones = [0] + [j for i in tones for j in i] + [0] word2ph = [1] + word2ph + [1] assert len(phones) == len(tones), text assert len(phones) == sum(word2ph), text return phones, tones, word2ph def get_bert_feature(text, word2ph): from text import english_bert_mock return english_bert_mock.get_bert_feature(text, word2ph) 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() # for k, syllables in eng_dict.items(): # for group in syllables: # for ph in group: # all_phones.add(ph) # print(all_phones)