import pickle import os import re from g2p_en import G2p from bert_vits2.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() 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 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 def text_normalize(text): return text def g2p(text): phones = [] tones = [] words = re.split(r"([,;.\-\?\!\s+])", text) for w in words: if w.upper() in eng_dict: phns, tns = refine_syllables(eng_dict[w.upper()]) phones += phns tones += tns else: phone_list = list(filter(lambda p: p != " ", _g2p(w))) for ph in phone_list: if ph in arpa: ph, tn = refine_ph(ph) phones.append(ph) tones.append(tn) else: phones.append(ph) tones.append(0) word2ph = [1 for i in phones] phones = [post_replace_ph(i) for i in phones] return phones, tones, 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)