import pickle import os import re from g2p_en import G2p 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() 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): # todo: eng text normalize 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) # todo: implement word2ph 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)