# SPDX-License-Identifier: Apache-2.0 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project """Lightweight text frontend aligned with the official GLM-TTS preprocessing.""" from __future__ import annotations import json import os import re try: import emoji except ImportError: emoji = None # type: ignore[assignment] try: import inflect except ImportError: inflect = None # type: ignore[assignment] try: from tn.chinese.normalizer import Normalizer as ZhNormalizer except ImportError: ZhNormalizer = None try: from tn.english.normalizer import Normalizer as EnNormalizer except ImportError: EnNormalizer = None CHINESE_CHAR_PATTERN = re.compile(r"[\u4e00-\u9fff]+") PUNCTUATION_CHARS = r"。？！；：、.?!;:，," def contains_chinese(text: str) -> bool: return bool(CHINESE_CHAR_PATTERN.search(text)) def markdown_norm(markdown_text: str) -> str: markdown_text = re.sub(r"^(\d+)\. ", r"\1。", markdown_text) return markdown_text.replace("\\n", "\n") def multi_line_process(plain_text: str) -> str: lines: list[str] = [] for line in plain_text.split("\n"): line = line.strip() if not line: continue if line[-1] not in {".", "!", "?", ";", ":", "：", "。", "！", "？", "；", "，"}: line = f"{line}{'。' if contains_chinese(line) else '. '}" lines.append(line) return "".join(lines) if contains_chinese("".join(lines)) else " ".join(lines) def remove_bracket(text: str, lang: str = "zh") -> str: brackets_to_remove = [ ("(", ")"), ("（", "）"), ("【", "】"), ("「", "」"), ("`", "`"), ("《", "》"), ("『", "』"), ("{", "}"), ("[", "]"), ] if lang != "en": brackets_to_remove.append(("‘", "’")) for left, right in brackets_to_remove: text = text.replace(left, "").replace(right, "") return text def number_to_chinese(number: int | float | str) -> str: units = ["", "十", "百", "千", "万", "十万", "百万", "千万", "亿", "十亿", "百亿", "千亿"] nums = "零一二三四五六七八九" if isinstance(number, (float, str)): str_num = str(float(number)) if "." in str_num: int_part, decimal_part = str_num.split(".") if decimal_part.strip("0") == "": return number_to_chinese(int(int_part)) chinese_int = number_to_chinese(int(int_part)) if int(int_part) != 0 else "零" chinese_decimal = "".join(nums[int(d)] for d in decimal_part) return f"{chinese_int}点{chinese_decimal}" number = int(number) if number == 0: return "零" if number < 0: return "负" + number_to_chinese(abs(number)) result: list[str] = [] unit_position = 0 zero_flag = False last_unit = "" while number > 0: num = number % 10 current_unit = units[unit_position] if unit_position < len(units) else "" if num == 0: if not zero_flag and result and last_unit not in ["万", "亿"]: result.append(nums[num]) zero_flag = True else: if current_unit: result.append(current_unit) result.append(nums[num]) zero_flag = False last_unit = current_unit unit_position += 1 number //= 10 result.reverse() text = "".join(result) text = re.sub(r"^一十", "十", text) text = re.sub(r"零+", "零", text) text = re.sub(r"零$", "", text) return text def tn_scientific_notation(text: str) -> str: pattern = re.compile(r"(.*?)(-?\d+(?:\.\d+)?)[*x×](\d+(?:\.\d+)?)\^(-?\d+(?:\.\d+)?)(.*?)$") match = pattern.match(text) if not match: return text prefix, base, multiplier, exponent, suffix = match.groups() description = f"{number_to_chinese(base)}乘{number_to_chinese(multiplier)}的{number_to_chinese(exponent)}次方" return f"{prefix}{description}{suffix}" def replace_asterisk_with_multiply(text: str, lang: str) -> str: if lang == "en": replace_name = "multiply" replace_number = "0-9" else: replace_name = "乘" replace_number = "一二三四五六七八九十百千万亿" rule0 = rf"(?<=[{replace_number}a-zA-Z])\s*\*\s*(?=[{replace_number}a-zA-Z])" rule1 = rf"(?<=[{replace_number}a-zA-Z]\))\s*\*\s*(?=[{replace_number}a-zA-Z])" rule2 = rf"(?<=[{replace_number}a-zA-Z])\s*\*\s*(?=\([{replace_number}a-zA-Z])" rule3 = rf"(?<=[{replace_number}a-zA-Z]\))\s*\*\s*(?=\([{replace_number}a-zA-Z])" return re.sub(f"{rule0}|{rule1}|{rule2}|{rule3}", replace_name, text).replace("*", "") def special_replace(text: str) -> str: text = text.replace("\\", "") text = f" {text} " text = re.sub(r"(?<=\W)额(?=\W)", "呃", text) text = re.sub(r"[~～]+", "。", text) text = replace_asterisk_with_multiply(text, "zh") return text.strip() def spell_out_number(text: str, inflect_parser: object | None) -> str: if inflect_parser is None: return text new_text: list[str] = [] start = None for idx, char in enumerate(text): if not char.isdigit(): if start is not None: new_text.append(inflect_parser.number_to_words(text[start:idx])) start = None new_text.append(char) elif start is None: start = idx if start is not None and start < len(text): new_text.append(inflect_parser.number_to_words(text[start:])) return "".join(new_text) def replace_space(text: str) -> str: alphanumeric_pattern = r"[a-zA-Z0-9]" punctuation_pattern = r"[.,!?;:]" text = re.sub(r" +", " ", text) result = "" idx = 0 while idx < len(text): current_char = text[idx] if current_char != " ": result += current_char idx += 1 continue prev_char = text[idx - 1] if idx > 0 else "" next_char = text[idx + 1] if idx + 1 < len(text) else "" if re.match(alphanumeric_pattern, prev_char) and re.match(alphanumeric_pattern, next_char): result += " " elif re.match(punctuation_pattern, prev_char) and re.match(alphanumeric_pattern, next_char): result += " " idx += 1 return result def normalize_punctuation(text: str, punctuation_chars: str) -> str: text = replace_space(text) text = re.sub(rf"([{punctuation_chars}])\1+", r"\1", text) text = re.sub(rf"([{punctuation_chars}])(?=[{punctuation_chars}])", "", text) text = text.replace("#", "") text = text.replace("！", "。") text = text.replace("!", ".") return text def ensure_proper_ending(text: str) -> str: if not text: return text if text[-1] in "？?": return text if text[-1] in PUNCTUATION_CHARS: return f"{text[:-1]}{'。' if contains_chinese(text) else '.'}" return f"{text}{'。' if contains_chinese(text) else '.'}" class GLMTTSTextFrontend: """Subset of the official GLM-TTS text frontend used by the adapter.""" def __init__(self) -> None: self.inflect_parser = inflect.engine() if inflect is not None else None self.zh_tn_model = ( ZhNormalizer( remove_erhua=False, full_to_half=True, remove_interjections=False, overwrite_cache=True, ) if ZhNormalizer is not None else None ) self.en_tn_model = EnNormalizer() if EnNormalizer is not None else None self._custom_replacements = self._load_custom_replacements() @staticmethod def _load_custom_replacements() -> list[tuple[str, str]]: custom_replace_path = os.path.join(os.path.dirname(__file__), "configs", "custom_replace.jsonl") if not os.path.exists(custom_replace_path): return [] replacements: list[tuple[str, str]] = [] with open(custom_replace_path, encoding="utf-8") as f: for line in f: if not line.strip(): continue item = json.loads(line) replacements.append((item["origin"], item["new"])) return replacements def pre_replace(self, sentence: str) -> str: sentence = tn_scientific_notation(sentence) sentence = re.sub(r"(?<=\d)\s*-\s*(?=\d)", "减", sentence) sentence = sentence.replace("-", "") sentence = re.sub(r"咯([" + re.escape(PUNCTUATION_CHARS) + r"])", r"喽\1", sentence) for origin, new in self._custom_replacements: sentence = sentence.replace(origin, new) return sentence def post_replace(self, sentence: str) -> str: sentence = remove_bracket(sentence) sentence = sentence.replace(" - ", "，") sentence = sentence.replace("——", "，") sentence = re.sub(r"[,:：;；、]+", "，", sentence) sentence = re.sub(r"[.…]+", "。", sentence) sentence = re.sub(r"[_·]+", "", sentence) sentence = re.sub(r"""['"‘’“”|]+""", "", sentence) symbol_map = { "†": "，", "²": "平方", "³": "立方", "/": "每", "~": "到", "～": "到", "①": "一", "②": "二", "③": "三", "④": "四", "⑤": "五", "⑥": "六", "⑦": "七", "⑧": "八", "⑨": "九", "⑩": "十", "α": "阿尔法", "β": "贝塔", "γ": "伽玛", "Γ": "伽玛", "δ": "德尔塔", "Δ": "德尔塔", "△": "德尔塔", "ε": "艾普西龙", "ζ": "捷塔", "η": "依塔", "θ": "西塔", "Θ": "西塔", "ι": "艾欧塔", "κ": "喀帕", "λ": "拉姆达", "Λ": "拉姆达", "μ": "缪", "ν": "拗", "ξ": "克西", "Ξ": "克西", "ο": "欧米克伦", "π": "派", "Π": "派", "ρ": "肉", "ς": "西格玛", "Σ": "西格玛", "σ": "西格玛", "τ": "套", "υ": "宇普西龙", "φ": "服艾", "Φ": "服艾", "χ": "器", "ψ": "普赛", "Ψ": "普赛", "ω": "欧米伽", "Ω": "欧米伽", "□": "方框", ">": "大于", "<": "小于", "∈": "属于", "∉": "不属于", "∪": "并", "∩": "交", "⊥": "垂直", "∥": "平行", "≠": "不等于", "∵": "因为", "∴": "所以", "∅": "空集", "⊂": "真包含于", "⊃": "包含", "⊆": "包含于", "⊇": "真包含", "⊄": "不属于", "⊅": "非超集", "⊈": "不属于", "⊉": "非超集", } for old, new in symbol_map.items(): sentence = sentence.replace(old, new) return sentence def text_normalize(self, text: str | None) -> str | None: if text is None: return None text = self._preprocess_text(text) if contains_chinese(text): text = self._normalize_chinese_text(text).lower() else: text = self._normalize_english_text(text) text = normalize_punctuation(text, PUNCTUATION_CHARS) return ensure_proper_ending(text) def _preprocess_text(self, text: str) -> str: text = markdown_norm(text) text = multi_line_process(text) if emoji is not None: text = emoji.replace_emoji(text, replace="") return re.sub(r"(?<=[a-zA-Z])-(?=[a-zA-Z])", " ", text) def _normalize_chinese_text(self, text: str) -> str: text = self.pre_replace(text) if self.zh_tn_model is not None: text = self.zh_tn_model.normalize(text) text = special_replace(text) return self.post_replace(text).strip() def _normalize_english_text(self, text: str) -> str: text = text.replace("'", "’") if self.en_tn_model is not None: text = self.en_tn_model.normalize(text) text = remove_bracket(text, "en") text = replace_asterisk_with_multiply(text, "en") text = text.replace("—", " ") text = text.replace("’", "'") text = spell_out_number(text, self.inflect_parser) text = re.sub(r"\s+", " ", text) keep_punctuation = r"\.,!\?'\:;" pattern = rf"[^\w\s{keep_punctuation}]" text = re.sub(pattern, "", text) text = text.lower() text = re.sub(r"\.+", ".", text) text = re.sub(r"\,+", ",", text) text = re.sub(r"!+", "!", text) text = re.sub(r"\?+", "?", text) text = re.sub(r"'+", "'", text) text = re.sub(r":+", ":", text) text = re.sub(r";+", ";", text) text = re.sub(r"\s*([.,?!':;])\s*", r"\1 ", text) return text.strip()