utils.py

from TTS.tts.models.vits import Vits
from TTS.tts.configs.vits_config import VitsConfig
import numpy as np
import unicodedata
import regex

num_re = regex.compile(r"([0-9.,]*[0-9])")
digits = ["không", "một", "hai", "ba", "bốn", "năm", "sáu", "bảy", "tám", "chín"]


def read_number(num: str) -> str:
    """Translate numeric text into written form

    Args: num (str) numeric text
    Returns: (str) written form of num
    """
    if len(num) == 1:
        return digits[int(num)]
    elif len(num) == 2 and num.isdigit():
        n = int(num)
        end = digits[n % 10]
        if n == 10:
            return "mười"
        if n % 10 == 5:
            end = "lăm"
        if n % 10 == 0:
            return digits[n // 10] + " mươi"
        elif n < 20:
            return "mười " + end
        else:
            if n % 10 == 1:
                end = "mốt"
            return digits[n // 10] + " mươi " + end
    elif len(num) == 3 and num.isdigit():
        n = int(num)
        if n % 100 == 0:
            return digits[n // 100] + " trăm"
        elif num[1] == "0":
            return digits[n // 100] + " trăm lẻ " + digits[n % 100]
        else:
            return digits[n // 100] + " trăm " + read_number(num[1:])
    elif 4 <= len(num) <= 6 and num.isdigit():
        n = int(num)
        n1 = n // 1000
        return read_number(str(n1)) + " ngàn " + read_number(num[-3:])
    elif "," in num:
        n1, n2 = num.split(",")
        return read_number(n1) + " phẩy " + read_number(n2)
    elif "." in num:
        parts = num.split(".")
        if len(parts) == 2:
            if parts[1] == "000":
                return read_number(parts[0]) + " ngàn"
            elif parts[1].startswith("00"):
                end = digits[int(parts[1][2:])]
                return read_number(parts[0]) + " ngàn lẻ " + end
            else:
                return read_number(parts[0]) + " ngàn " + read_number(parts[1])
        elif len(parts) == 3:
            return (
                    read_number(parts[0])
                    + " triệu "
                    + read_number(parts[1])
                    + " ngàn "
                    + read_number(parts[2])
            )
    return num


def load_model():
    config = VitsConfig()
    config.load_json("vits/config.json")
    vits = Vits.init_from_config(config)

    vits.load_onnx("vits/coqui_vits.onnx")

    text = "xin chào tôi là hoàng đây"
    text_inputs = np.asarray(
        vits.tokenizer.text_to_ids(text),
        dtype=np.int64,
    )[None, :]

    audio = vits.inference_onnx(text_inputs)

    return vits


def normalize_text(text):
    """Normalize the input text

    Args: text (str) the input text
    Returns: text (str) the normalized text
    """
    # lowercase
    text = text.lower()
    # unicode normalize
    text = unicodedata.normalize("NFKC", text)
    text = text.replace(".", "")
    text = text.replace(",", "")
    text = text.replace(";", "")
    text = text.replace(":", "")
    text = text.replace("!", "")
    text = text.replace("?", "")
    text = text.replace("(", "")
    # Convert numeric text into written form
    text = num_re.sub(r" \1 ", text)
    words = text.split()
    words = [read_number(w) if num_re.fullmatch(w) else w for w in words]
    text = " ".join(words)

    return text