diff --git a/GPT_SoVITS/prepare_datasets/1-get-text.py b/GPT_SoVITS/prepare_datasets/1-get-text.py
index bdeacc7..76a2d69 100644
--- a/GPT_SoVITS/prepare_datasets/1-get-text.py
+++ b/GPT_SoVITS/prepare_datasets/1-get-text.py
@@ -1,6 +1,9 @@
 # -*- coding: utf-8 -*-
 
 import os
+import re
+import LangSegment
+from text import chinese
 
 inp_text = os.environ.get("inp_text")
 inp_wav_dir = os.environ.get("inp_wav_dir")
@@ -83,24 +86,104 @@ if os.path.exists(txt_path) == False:
 
         return phone_level_feature.T
 
+    def get_bert_inf(phones:list, word2ph:list, norm_text:str, language:str):
+        language=language.replace("all_","")
+        if language == "zh":
+            feature = get_bert_feature(norm_text, word2ph).to(device)
+        else:
+            feature = torch.zeros(
+                (1024, len(phones)),
+                dtype=torch.float32,
+            ).to(device)
+
+        return feature
+
+    def get_phones_and_bert(text:str, language:str, version:str, final:bool=False):
+        if language in {"en", "all_zh", "all_ja", "all_ko", "all_yue"}:
+            language = language.replace("all_","")
+            if language == "en":
+                LangSegment.setfilters(["en"])
+                formattext = " ".join(tmp["text"] for tmp in LangSegment.getTexts(text))
+            else:
+                # 因无法区别中日韩文汉字,以用户输入为准
+                formattext = text
+            while "  " in formattext:
+                formattext = formattext.replace("  ", " ")
+            if language == "zh":
+                if re.search(r'[A-Za-z]', formattext):
+                    formattext = re.sub(r'[a-z]', lambda x: x.group(0).upper(), formattext)
+                    formattext = chinese.mix_text_normalize(formattext)
+                    return get_phones_and_bert(formattext,"zh",version)
+                else:
+                    phones, word2ph, norm_text = clean_text(formattext, language, version)
+                    bert = get_bert_feature(norm_text, word2ph).to(device)
+            elif language == "yue" and re.search(r'[A-Za-z]', formattext):
+                    formattext = re.sub(r'[a-z]', lambda x: x.group(0).upper(), formattext)
+                    formattext = chinese.mix_text_normalize(formattext)
+                    return get_phones_and_bert(formattext,"yue",version)
+            else:
+                phones, word2ph, norm_text = clean_text(formattext, language, version)
+                bert = torch.zeros(
+                    (1024, len(phones)),
+                    dtype=torch.float32,
+                ).to(device)
+        elif language in {"zh", "ja", "ko", "yue", "auto", "auto_yue"}:
+            textlist=[]
+            langlist=[]
+            LangSegment.setfilters(["zh","ja","en","ko"])
+            if language == "auto":
+                for tmp in LangSegment.getTexts(text):
+                    langlist.append(tmp["lang"])
+                    textlist.append(tmp["text"])
+            elif language == "auto_yue":
+                for tmp in LangSegment.getTexts(text):
+                    if tmp["lang"] == "zh":
+                        tmp["lang"] = "yue"
+                    langlist.append(tmp["lang"])
+                    textlist.append(tmp["text"])
+            else:
+                for tmp in LangSegment.getTexts(text):
+                    if tmp["lang"] == "en":
+                        langlist.append(tmp["lang"])
+                    else:
+                        # 因无法区别中日韩文汉字,以用户输入为准
+                        langlist.append(language)
+                    textlist.append(tmp["text"])
+            # print(textlist)
+            # print(langlist)
+            phones_list = []
+            bert_list = []
+            norm_text_list = []
+            for i in range(len(textlist)):
+                lang = langlist[i]
+                phones, word2ph, norm_text = clean_text(textlist[i], lang, version)
+                bert = get_bert_inf(phones, word2ph, norm_text, lang)
+                phones_list.append(phones)
+                norm_text_list.append(norm_text)
+                bert_list.append(bert)
+            bert = torch.cat(bert_list, dim=1)
+            phones = sum(phones_list, [])
+            norm_text = ''.join(norm_text_list)
+
+        return phones, bert, norm_text
+
     def process(data, res):
         for name, text, lan in data:
             try:
                 name=clean_path(name)
                 name = os.path.basename(name)
                 print(name)
-                phones, word2ph, norm_text = clean_text(
-                    text.replace("%", "-").replace("￥", ","), lan, version
+                phones, bert_feature, norm_text = get_phones_and_bert(
+                    text.replace("%", "-").replace("￥", ","), lan, 'v2'
                 )
                 path_bert = "%s/%s.pt" % (bert_dir, name)
                 if os.path.exists(path_bert) == False and lan == "zh":
-                    bert_feature = get_bert_feature(norm_text, word2ph)
                     assert bert_feature.shape[-1] == len(phones)
                     # torch.save(bert_feature, path_bert)
                     my_save(bert_feature, path_bert)
                 phones = " ".join(phones)
                 # res.append([name,phones])
-                res.append([name, phones, word2ph, norm_text])
+                res.append([name, phones, None, norm_text])
             except:
                 print(name, text, traceback.format_exc())