不同版本Onnx模型导出适配 (#221)
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Ναρουσέ·μ·γιουμεμί·Χινακάννα
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onnx_modules/V200/text/english.py
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362
onnx_modules/V200/text/english.py
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import pickle
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import os
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import re
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from g2p_en import G2p
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from . import symbols
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current_file_path = os.path.dirname(__file__)
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CMU_DICT_PATH = os.path.join(current_file_path, "cmudict.rep")
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CACHE_PATH = os.path.join(current_file_path, "cmudict_cache.pickle")
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_g2p = G2p()
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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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def post_replace_ph(ph):
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rep_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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"v": "V",
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}
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if ph in rep_map.keys():
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ph = rep_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():
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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, file_path):
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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():
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if os.path.exists(CACHE_PATH):
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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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eng_dict = get_dict()
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def refine_ph(phn):
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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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return phn.lower(), tone
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def refine_syllables(syllables):
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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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import re
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import inflect
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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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# List of (regular expression, replacement) pairs for abbreviations:
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_abbreviations = [
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(re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
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for x in [
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("mrs", "misess"),
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("mr", "mister"),
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("dr", "doctor"),
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("st", "saint"),
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("co", "company"),
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("jr", "junior"),
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("maj", "major"),
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("gen", "general"),
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("drs", "doctors"),
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("rev", "reverend"),
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("lt", "lieutenant"),
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("hon", "honorable"),
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("sgt", "sergeant"),
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("capt", "captain"),
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("esq", "esquire"),
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("ltd", "limited"),
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("col", "colonel"),
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("ft", "fort"),
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]
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]
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# List of (ipa, lazy ipa) pairs:
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_lazy_ipa = [
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(re.compile("%s" % x[0]), x[1])
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for x in [
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("r", "ɹ"),
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("æ", "e"),
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("ɑ", "a"),
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("ɔ", "o"),
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("ð", "z"),
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("θ", "s"),
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("ɛ", "e"),
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("ɪ", "i"),
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("ʊ", "u"),
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("ʒ", "ʥ"),
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("ʤ", "ʥ"),
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("ˈ", "↓"),
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]
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]
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# List of (ipa, lazy ipa2) pairs:
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_lazy_ipa2 = [
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(re.compile("%s" % x[0]), x[1])
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for x in [
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("r", "ɹ"),
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("ð", "z"),
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("θ", "s"),
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("ʒ", "ʑ"),
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("ʤ", "dʑ"),
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("ˈ", "↓"),
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]
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]
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# List of (ipa, ipa2) pairs
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_ipa_to_ipa2 = [
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(re.compile("%s" % x[0]), x[1]) for x in [("r", "ɹ"), ("ʤ", "dʒ"), ("ʧ", "tʃ")]
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]
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def _expand_dollars(m):
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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):
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return m.group(1).replace(",", "")
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def _expand_ordinal(m):
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return _inflect.number_to_words(m.group(0))
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def _expand_number(m):
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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)
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elif num % 100 == 0:
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return _inflect.number_to_words(num // 100) + " hundred"
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else:
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return _inflect.number_to_words(
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num, andword="", zero="oh", group=2
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).replace(", ", " ")
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else:
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return _inflect.number_to_words(num, andword="")
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def _expand_decimal_point(m):
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return m.group(1).replace(".", " point ")
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def normalize_numbers(text):
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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 text_normalize(text):
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text = normalize_numbers(text)
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return text
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def g2p(text):
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phones = []
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tones = []
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word2ph = []
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words = re.split(r"([,;.\-\?\!\s+])", text)
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words = [word for word in words if word.strip() != ""]
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for word in words:
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if word.upper() in eng_dict:
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phns, tns = refine_syllables(eng_dict[word.upper()])
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phones += phns
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tones += tns
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word2ph.append(len(phns))
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else:
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phone_list = list(filter(lambda p: p != " ", _g2p(word)))
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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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phones.append(ph)
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tones.append(tn)
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else:
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phones.append(ph)
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tones.append(0)
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word2ph.append(len(phone_list))
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phones = [post_replace_ph(i) for i in phones]
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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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return phones, tones, word2ph
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def get_bert_feature(text, word2ph):
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from text import english_bert_mock
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return english_bert_mock.get_bert_feature(text, word2ph)
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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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# 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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