64 lines
1.9 KiB
Python
64 lines
1.9 KiB
Python
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from ..text.symbols import *
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_symbol_to_id = {s: i for i, s in enumerate(symbols)}
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def cleaned_text_to_sequence(cleaned_text, tones, language):
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"""Converts a string of text to a sequence of IDs corresponding to the symbols in the text.
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Args:
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text: string to convert to a sequence
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Returns:
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List of integers corresponding to the symbols in the text
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"""
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phones = [_symbol_to_id[symbol] for symbol in cleaned_text]
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tone_start = language_tone_start_map[language]
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tones = [i + tone_start for i in tones]
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lang_id = language_id_map[language]
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lang_ids = [lang_id for i in phones]
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return phones, tones, lang_ids
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def get_bert(norm_text, word2ph, language, device, style_text=None, style_weight=0.7):
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from .chinese_bert import get_bert_feature as zh_bert
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from .english_bert_mock import get_bert_feature as en_bert
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from .japanese_bert import get_bert_feature as jp_bert
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lang_bert_func_map = {"ZH": zh_bert, "EN": en_bert, "JP": jp_bert}
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bert = lang_bert_func_map[language](
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norm_text, word2ph, device, style_text, style_weight
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)
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return bert
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def check_bert_models():
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relative_path = r"./utils/bert_vits2/"
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import json
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from pathlib import Path
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from ..config import config
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from .bert_utils import _check_bert
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if config.mirror.lower() == "openi":
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import openi
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kwargs = {"token": config.openi_token} if config.openi_token else {}
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openi.login(**kwargs)
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with open(relative_path+"bert/bert_models.json", "r") as fp:
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models = json.load(fp)
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for k, v in models.items():
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local_path = Path(relative_path+"bert").joinpath(k)
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_check_bert(v["repo_id"], v["files"], local_path)
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def init_openjtalk():
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import platform
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if platform.platform() == "Linux":
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import pyopenjtalk
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pyopenjtalk.g2p("こんにちは，世界。")
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init_openjtalk()
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check_bert_models()
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