From b6b63936c7f4320b30b5f907514f6e8d39ed7239 Mon Sep 17 00:00:00 2001
From: mengzhe.cmz <mengzhe.cmz@alibaba-inc.com>
Date: 星期二, 18 七月 2023 17:32:38 +0800
Subject: [PATCH] add punc large model modelscope runtime; fix train bug

---
 funasr/datasets/preprocessor.py |   69 +++++++++++++++++++++++++++++++++-
 1 files changed, 67 insertions(+), 2 deletions(-)

diff --git a/funasr/datasets/preprocessor.py b/funasr/datasets/preprocessor.py
index cb4288c..c6623f8 100644
--- a/funasr/datasets/preprocessor.py
+++ b/funasr/datasets/preprocessor.py
@@ -11,6 +11,7 @@
 import numpy as np
 import scipy.signal
 import soundfile
+import jieba
 
 from funasr.text.build_tokenizer import build_tokenizer
 from funasr.text.cleaner import TextCleaner
@@ -628,6 +629,7 @@
             text_name: str = "text",
             split_text_name: str = "split_text",
             split_with_space: bool = False,
+            seg_jieba: bool = False,
             seg_dict_file: str = None,
     ):
         super().__init__(
@@ -655,6 +657,9 @@
         )
         # The data field name for split text.
         self.split_text_name = split_text_name
+        self.seg_jieba = seg_jieba
+        if self.seg_jieba:
+            jieba.load_userdict(seg_dict_file)
 
     @classmethod
     def split_words(cls, text: str):
@@ -677,12 +682,73 @@
                 words.append(current_word)
         return words
 
+    @classmethod
+    def isEnglish(cls, text:str):
+        if re.search('^[a-zA-Z\']+$', text):
+            return True
+        else:
+            return False
+
+    @classmethod
+    def join_chinese_and_english(cls, input_list):
+        line = ''
+        for token in input_list:
+            if cls.isEnglish(token):
+                line = line + ' ' + token
+            else:
+                line = line + token
+
+        line = line.strip()
+        return line   
+
+    @classmethod
+    def split_words_jieba(cls, text: str):
+        input_list = text.split()
+        token_list_all = []
+        langauge_list = []
+        token_list_tmp = []
+        language_flag = None
+        for token in input_list:
+            if cls.isEnglish(token) and language_flag == 'Chinese':
+                token_list_all.append(token_list_tmp)
+                langauge_list.append('Chinese')
+                token_list_tmp = []
+            elif not cls.isEnglish(token) and language_flag == 'English':
+                token_list_all.append(token_list_tmp)
+                langauge_list.append('English')
+                token_list_tmp = []
+
+            token_list_tmp.append(token)
+
+            if cls.isEnglish(token):
+                language_flag = 'English'
+            else:
+                language_flag = 'Chinese'
+
+        if token_list_tmp:
+            token_list_all.append(token_list_tmp)
+            langauge_list.append(language_flag)
+
+        result_list = []
+        for token_list_tmp, language_flag in zip(token_list_all, langauge_list):
+            if language_flag == 'English':
+                result_list.extend(token_list_tmp)
+            else:
+                seg_list = jieba.cut(cls.join_chinese_and_english(token_list_tmp), HMM=False)
+                result_list.extend(seg_list)
+
+        return result_list
+
     def __call__(
             self, uid: str, data: Dict[str, Union[list, str, np.ndarray]]
     ) -> Dict[str, Union[list, np.ndarray]]:
         # Split words.
         if isinstance(data[self.text_name], str):
-            split_text = self.split_words(data[self.text_name])
+            if self.seg_jieba:
+  #              jieba.load_userdict(seg_dict_file)
+                split_text = self.split_words_jieba(data[self.text_name])
+            else:
+                split_text = self.split_words(data[self.text_name])
         else:
             split_text = data[self.text_name]
         data[self.text_name] = " ".join(split_text)
@@ -782,7 +848,6 @@
     ) -> Dict[str, np.ndarray]:
         for i in range(self.num_tokenizer):
             text_name = self.text_name[i]
-            #import pdb; pdb.set_trace()
             if text_name in data and self.tokenizer[i] is not None:
                 text = data[text_name]
                 text = self.text_cleaner(text)

--
Gitblit v1.9.1