sbv2-v2/style_bert_vits2/nlp/english/__init__.py

import pickle
import os
import re
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


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


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]
    else:
        tone = 3
    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 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 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 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 text_to_words(text):
    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


def g2p(text: str) -> tuple[list[str], list[int], list[int]]:
    phones = []
    tones = []
    phone_len = []
    # words = sep_text(text)
    # tokens = [tokenizer.tokenize(i) for i in words]
    words = text_to_words(text)

    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)))
                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


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)