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from text.symbols import *
_symbol_to_id = {s: i for i, s in enumerate(symbols)}
def cleaned_text_to_sequence(cleaned_text, tones, language):
"""Converts a string of text to a sequence of IDs corresponding to the symbols in the text.
Args:
text: string to convert to a sequence
Returns:
List of integers corresponding to the symbols in the text
"""
phones = [_symbol_to_id[symbol] for symbol in cleaned_text]
tone_start = language_tone_start_map[language]
tones = [i + tone_start for i in tones]
lang_id = language_id_map[language]
lang_ids = [lang_id for i in phones]
return phones, tones, lang_ids
def get_bert(norm_text, word2ph, language, device):
from .chinese_bert import get_bert_feature as zh_bert
from .english_bert_mock import get_bert_feature as en_bert
from .japanese_bert import get_bert_feature as jp_bert
lang_bert_func_map = {"ZH": zh_bert, "EN": en_bert, "JP": jp_bert}
bert = lang_bert_func_map[language](norm_text, word2ph, device)
return bert
def check_bert_models():
import json
from pathlib import Path
from config import config
from .bert_utils import _check_bert
if config.mirror.lower() == "openi":
import openi
kwargs = {"token": config.openi_token} if config.openi_token else {}
openi.login(**kwargs)
with open("./bert/bert_models.json", "r") as fp:
models = json.load(fp)
for k, v in models.items():
local_path = Path("./bert").joinpath(k)
_check_bert(v["repo_id"], v["files"], local_path)
def init_openjtalk():
import platform
if platform.platform() == "Linux":
import pyopenjtalk
pyopenjtalk.g2p("こんにちは，世界。")
init_openjtalk()
check_bert_models()
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