Refactor: split style_bert_vits2.nlp.chinese package

Configured so that the same public function is exported from the module with the same name for each language.

style_bert_vits2/nlp/chinese/normalizer.py

@@ -0,0 +1,61 @@
+import re
+
+import cn2an
+
+from style_bert_vits2.nlp.symbols import PUNCTUATIONS
+
+
+def normalize_text(text: str) -> str:
+    numbers = re.findall(r"\d+(?:\.?\d+)?", text)
+    for number in numbers:
+        text = text.replace(number, cn2an.an2cn(number), 1)
+    text = replace_punctuation(text)
+    return text
+
+
+def replace_punctuation(text: str) -> str:
+
+    REPLACE_MAP = {
+        "：": ",",
+        "；": ",",
+        "，": ",",
+        "。": ".",
+        "！": "!",
+        "？": "?",
+        "\n": ".",
+        "·": ",",
+        "、": ",",
+        "...": "…",
+        "$": ".",
+        "“": "'",
+        "”": "'",
+        '"': "'",
+        "‘": "'",
+        "’": "'",
+        "（": "'",
+        "）": "'",
+        "(": "'",
+        ")": "'",
+        "《": "'",
+        "》": "'",
+        "【": "'",
+        "】": "'",
+        "[": "'",
+        "]": "'",
+        "—": "-",
+        "～": "-",
+        "~": "-",
+        "「": "'",
+        "」": "'",
+    }
+
+    text = text.replace("嗯", "恩").replace("呣", "母")
+    pattern = re.compile("|".join(re.escape(p) for p in REPLACE_MAP.keys()))
+
+    replaced_text = pattern.sub(lambda x: REPLACE_MAP[x.group()], text)
+
+    replaced_text = re.sub(
+        r"[^\u4e00-\u9fa5" + "".join(PUNCTUATIONS) + r"]+", "", replaced_text
+    )
+
+    return replaced_text