Better normlization (#1351)

GPT_SoVITS/inference_webui.py

@@ -236,7 +236,7 @@ def get_first(text):
     text = re.split(pattern, text)[0].strip()
     return text
 
-
+from text import chinese
 def get_phones_and_bert(text,language):
     if language in {"en","all_zh","all_ja"}:
         language = language.replace("all_","")
@@ -248,10 +248,17 @@ def get_phones_and_bert(text,language):
             formattext = text
         while "  " in formattext:
             formattext = formattext.replace("  ", " ")
-        phones, word2ph, norm_text = clean_text_inf(formattext, language)
         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.text_normalize(formattext)
+                return get_phones_and_bert(formattext,"zh")
+            else:
+                phones, word2ph, norm_text = clean_text_inf(formattext, language)
+
             bert = get_bert_feature(norm_text, word2ph).to(device)
         else:
+            phones, word2ph, norm_text = clean_text_inf(formattext, language)
             bert = torch.zeros(
                 (1024, len(phones)),
                 dtype=torch.float16 if is_half == True else torch.float32,
@@ -327,7 +334,6 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language,
         if (prompt_text[-1] not in splits): prompt_text += "。" if prompt_language != "en" else "."
         print(i18n("实际输入的参考文本:"), prompt_text)
     text = text.strip("\n")
-    text = replace_consecutive_punctuation(text)
     if (text[0] not in splits and len(get_first(text)) < 4): text = "。" + text if text_language != "en" else "." + text
     
     print(i18n("实际输入的目标文本:"), text)
@@ -551,13 +557,6 @@ def process_text(texts):
     return _text
 
 
-def replace_consecutive_punctuation(text):
-    punctuations = ''.join(re.escape(p) for p in punctuation)
-    pattern = f'([{punctuations}])([{punctuations}])+'
-    result = re.sub(pattern, r'\1', text)
-    return result
-
-
 def change_choices():
     SoVITS_names, GPT_names = get_weights_names()
     return {"choices": sorted(SoVITS_names, key=custom_sort_key), "__type__": "update"}, {"choices": sorted(GPT_names, key=custom_sort_key), "__type__": "update"}

GPT_SoVITS/text/chinese.py

@@ -48,12 +48,19 @@ def replace_punctuation(text):
     replaced_text = pattern.sub(lambda x: rep_map[x.group()], text)
 
     replaced_text = re.sub(
-        r"[^\u4e00-\u9fa5" + "".join(punctuation) + r"]+", "", replaced_text
+        r"[^\u4e00-\u9fa5A-Za-z" + "".join(punctuation) + r"]+", "", replaced_text
     )
 
     return replaced_text
 
 
+def replace_consecutive_punctuation(text):
+    punctuations = ''.join(re.escape(p) for p in punctuation)
+    pattern = f'([{punctuations}])([{punctuations}])+'
+    result = re.sub(pattern, r'\1', text)
+    return result
+
+
 def g2p(text):
     pattern = r"(?<=[{0}])\s*".format("".join(punctuation))
     sentences = [i for i in re.split(pattern, text) if i.strip() != ""]
@@ -158,6 +165,9 @@ def text_normalize(text):
     dest_text = ""
     for sentence in sentences:
         dest_text += replace_punctuation(sentence)
+
+    # 避免重复标点引起的参考泄露
+    dest_text = replace_consecutive_punctuation(dest_text)
     return dest_text
 
 

GPT_SoVITS/text/english.py

@@ -4,7 +4,7 @@ import re
 import wordsegment
 from g2p_en import G2p
 
-from string import punctuation
+from text.symbols import punctuation
 
 from text import symbols
 
@@ -110,6 +110,13 @@ def replace_phs(phs):
     return phs_new
 
 
+def replace_consecutive_punctuation(text):
+    punctuations = ''.join(re.escape(p) for p in punctuation)
+    pattern = f'([{punctuations}])([{punctuations}])+'
+    result = re.sub(pattern, r'\1', text)
+    return result
+
+
 def read_dict():
     g2p_dict = {}
     start_line = 49
@@ -234,6 +241,9 @@ def text_normalize(text):
     text = re.sub(r"(?i)i\.e\.", "that is", text)
     text = re.sub(r"(?i)e\.g\.", "for example", text)
 
+    # 避免重复标点引起的参考泄露
+    text = replace_consecutive_punctuation(text)
+
     return text
 
 

GPT_SoVITS/text/japanese.py

@@ -6,6 +6,7 @@ import pyopenjtalk
 
 
 from text import symbols
+from text.symbols import punctuation
 # Regular expression matching Japanese without punctuation marks:
 _japanese_characters = re.compile(
     r"[A-Za-z\d\u3005\u3040-\u30ff\u4e00-\u9fff\uff11-\uff19\uff21-\uff3a\uff41-\uff5a\uff66-\uff9d]"
@@ -65,6 +66,13 @@ def post_replace_ph(ph):
     return ph
 
 
+def replace_consecutive_punctuation(text):
+    punctuations = ''.join(re.escape(p) for p in punctuation)
+    pattern = f'([{punctuations}])([{punctuations}])+'
+    result = re.sub(pattern, r'\1', text)
+    return result
+
+
 def symbols_to_japanese(text):
     for regex, replacement in _symbols_to_japanese:
         text = re.sub(regex, replacement, text)
@@ -94,6 +102,9 @@ def preprocess_jap(text, with_prosody=False):
 
 def text_normalize(text):
     # todo: jap text normalize
+
+    # 避免重复标点引起的参考泄露
+    text = replace_consecutive_punctuation(text)
     return text
 
 # Copied from espnet https://github.com/espnet/espnet/blob/master/espnet2/text/phoneme_tokenizer.py

GPT_SoVITS/text/zh_normalization/num.py

@@ -107,8 +107,11 @@ def replace_default_num(match):
 
 
 # 加减乘除
+# RE_ASMD = re.compile(
+#     r'((-?)((\d+)(\.\d+)?)|(\.(\d+)))([\+\-\×÷=])((-?)((\d+)(\.\d+)?)|(\.(\d+)))')
 RE_ASMD = re.compile(
-    r'((-?)((\d+)(\.\d+)?)|(\.(\d+)))([\+\-\×÷=])((-?)((\d+)(\.\d+)?)|(\.(\d+)))')
+    r'((-?)((\d+)(\.\d+)?[⁰¹²³⁴⁵⁶⁷⁸⁹ˣʸⁿ]*)|(\.\d+[⁰¹²³⁴⁵⁶⁷⁸⁹ˣʸⁿ]*)|([A-Za-z][⁰¹²³⁴⁵⁶⁷⁸⁹ˣʸⁿ]*))([\+\-\×÷=])((-?)((\d+)(\.\d+)?[⁰¹²³⁴⁵⁶⁷⁸⁹ˣʸⁿ]*)|(\.\d+[⁰¹²³⁴⁵⁶⁷⁸⁹ˣʸⁿ]*)|([A-Za-z][⁰¹²³⁴⁵⁶⁷⁸⁹ˣʸⁿ]*))')
+
 asmd_map = {
     '+': '加',
     '-': '减',
@@ -117,7 +120,6 @@ asmd_map = {
     '=': '等于'
 }
 
-
 def replace_asmd(match) -> str:
     """
     Args:
@@ -129,6 +131,39 @@ def replace_asmd(match) -> str:
     return result
 
 
+# 次方专项
+RE_POWER = re.compile(r'[⁰¹²³⁴⁵⁶⁷⁸⁹ˣʸⁿ]+')
+
+power_map = {
+    '⁰': '0',
+    '¹': '1',
+    '²': '2',
+    '³': '3',
+    '⁴': '4',
+    '⁵': '5',
+    '⁶': '6',
+    '⁷': '7',
+    '⁸': '8',
+    '⁹': '9',
+    'ˣ': 'x',
+    'ʸ': 'y',
+    'ⁿ': 'n'
+}
+
+def replace_power(match) -> str:
+    """
+    Args:
+        match (re.Match)
+    Returns:
+        str
+    """
+    power_num = ""
+    for m in match.group(0):
+        power_num += power_map[m]
+    result = "的" + power_num + "次方"
+    return result
+
+
 # 数字表达式
 # 纯小数
 RE_DECIMAL_NUM = re.compile(r'(-?)((\d+)(\.\d+))' r'|(\.(\d+))')

GPT_SoVITS/text/zh_normalization/text_normlization.py

@@ -35,6 +35,7 @@ from .num import RE_POSITIVE_QUANTIFIERS
 from .num import RE_RANGE
 from .num import RE_TO_RANGE
 from .num import RE_ASMD
+from .num import RE_POWER
 from .num import replace_default_num
 from .num import replace_frac
 from .num import replace_negative_num
@@ -44,6 +45,7 @@ from .num import replace_positive_quantifier
 from .num import replace_range
 from .num import replace_to_range
 from .num import replace_asmd
+from .num import replace_power
 from .phonecode import RE_MOBILE_PHONE
 from .phonecode import RE_NATIONAL_UNIFORM_NUMBER
 from .phonecode import RE_TELEPHONE
@@ -114,6 +116,12 @@ class TextNormalizer():
         sentence = sentence.replace('χ', '器')
         sentence = sentence.replace('ψ', '普赛').replace('Ψ', '普赛')
         sentence = sentence.replace('ω', '欧米伽').replace('Ω', '欧米伽')
+        # 兜底数学运算，顺便兼容懒人用语
+        sentence = sentence.replace('+', '加')
+        sentence = sentence.replace('-', '减')
+        sentence = sentence.replace('×', '乘')
+        sentence = sentence.replace('÷', '除')
+        sentence = sentence.replace('=', '等')
         # re filter special characters, have one more character "-" than line 68
         sentence = re.sub(r'[-——《》【】<=>{}()（）#&@“”^_|\\]', '', sentence)
         return sentence
@@ -136,6 +144,12 @@ class TextNormalizer():
         sentence = RE_TO_RANGE.sub(replace_to_range, sentence)
         sentence = RE_TEMPERATURE.sub(replace_temperature, sentence)
         sentence = replace_measure(sentence)
+
+        # 处理数学运算
+        while RE_ASMD.search(sentence):
+            sentence = RE_ASMD.sub(replace_asmd, sentence)
+        sentence = RE_POWER.sub(replace_power, sentence)
+
         sentence = RE_FRAC.sub(replace_frac, sentence)
         sentence = RE_PERCENTAGE.sub(replace_percentage, sentence)
         sentence = RE_MOBILE_PHONE.sub(replace_mobile, sentence)
@@ -145,10 +159,6 @@ class TextNormalizer():
 
         sentence = RE_RANGE.sub(replace_range, sentence)
 
-        # 处理加减乘除
-        while RE_ASMD.search(sentence):
-            sentence = RE_ASMD.sub(replace_asmd, sentence)
-
         sentence = RE_INTEGER.sub(replace_negative_num, sentence)
         sentence = RE_DECIMAL_NUM.sub(replace_number, sentence)
         sentence = RE_POSITIVE_QUANTIFIERS.sub(replace_positive_quantifier,