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| import regex as re | |
| import logging | |
| import config | |
| from .utils import check_is_none | |
| logger = logging.getLogger("vits-simple-api") | |
| level = getattr(config, "LOGGING_LEVEL", "DEBUG") | |
| level_dict = {'DEBUG': logging.DEBUG, 'INFO': logging.INFO, 'WARNING': logging.WARNING, 'ERROR': logging.ERROR, | |
| 'CRITICAL': logging.CRITICAL} | |
| logger.setLevel(level_dict[level]) | |
| def clasify_lang(text, speaker_lang): | |
| pattern = r'[\!\"\#\$\%\&\'\(\)\*\+\,\-\.\/\:\;\<\>\=\?\@\[\]\{\}\\\\\^\_\`' \ | |
| r'\！？｡＂＃＄％＆＇（）＊＋，－／：；＜＝＞＠［＼］＾＿｀｛｜｝～｟｠｢｣､、〃》「」' \ | |
| r'『』【】〔〕〖〗〘〙〚〛〜〝〞〟〰〾〿–—‘\'\‛\“\”\„\‟…‧﹏.]+' | |
| words = re.split(pattern, text) | |
| pre = "" | |
| p = 0 | |
| for word in words: | |
| if check_is_none(word): continue | |
| # 读取配置选择语种识别库 | |
| clf = getattr(config, "LANGUAGE_IDENTIFICATION_LIBRARY", "fastlid") | |
| if clf.upper() == "FASTLID" or clf.upper() == "FASTTEXT": | |
| from fastlid import fastlid | |
| lang = fastlid(word)[0] | |
| if speaker_lang != None: fastlid.set_languages = speaker_lang | |
| elif clf.upper() == "LANGID": | |
| import langid | |
| lang = langid.classify(word)[0] | |
| if speaker_lang != None: langid.set_languages(speaker_lang) | |
| else: | |
| raise ValueError(f"Wrong LANGUAGE_IDENTIFICATION_LIBRARY in config.py") | |
| if pre == "": | |
| text = text[:p] + text[p:].replace(word, f'[{lang.upper()}]' + word, 1) | |
| p += len(f'[{lang.upper()}]') | |
| elif pre != lang: | |
| text = text[:p] + text[p:].replace(word, f'[{pre.upper()}][{lang.upper()}]' + word, 1) | |
| p += len(f'[{pre.upper()}][{lang.upper()}]') | |
| pre = lang | |
| p += text[p:].index(word) + len(word) | |
| text += f"[{pre.upper()}]" | |
| return text | |
| def cut(text, max): | |
| pattern = r'[!(),—+\-.:;?？。，、；：]+' | |
| sentences = re.split(pattern, text) | |
| discarded_chars = re.findall(pattern, text) | |
| sentence_list, count, p = [], 0, 0 | |
| # 按被分割的符号遍历 | |
| for i, discarded_chars in enumerate(discarded_chars): | |
| count += len(sentences[i]) + len(discarded_chars) | |
| if count >= max: | |
| sentence_list.append(text[p:p + count].strip()) | |
| p += count | |
| count = 0 | |
| # 加入最后剩余的文本 | |
| if p < len(text): | |
| sentence_list.append(text[p:]) | |
| return sentence_list | |
| def sentence_split(text, max=50, lang="auto", speaker_lang=None): | |
| # 如果该speaker只支持一种语言 | |
| if speaker_lang is not None and len(speaker_lang) == 1: | |
| if lang.upper() not in ["AUTO", "MIX"] and lang.lower() != speaker_lang[0]: | |
| logger.debug( | |
| f"lang \"{lang}\" is not in speaker_lang {speaker_lang},automatically set lang={speaker_lang[0]}") | |
| lang = speaker_lang[0] | |
| sentence_list = [] | |
| if lang.upper() != "MIX": | |
| if max <= 0: | |
| sentence_list.append( | |
| clasify_lang(text, | |
| speaker_lang) if lang.upper() == "AUTO" else f"[{lang.upper()}]{text}[{lang.upper()}]") | |
| else: | |
| for i in cut(text, max): | |
| if check_is_none(i): continue | |
| sentence_list.append( | |
| clasify_lang(i, | |
| speaker_lang) if lang.upper() == "AUTO" else f"[{lang.upper()}]{i}[{lang.upper()}]") | |
| else: | |
| sentence_list.append(text) | |
| for i in sentence_list: | |
| logger.debug(i) | |
| return sentence_list | |