""" 控制标记解析器（Control Markup Parser） ======================================== 把带控制标记的文本解析成一串「片段」，每个片段要么是一段需要用某条参考语音 合成的语音（speech），要么是一段静音停顿（silence）。这一步对应书中「执行层 解析标记并映射到对应的参考语音」。 支持两类标记： 1) 状态标记（持续生效，直到被下一个同类标记改变） [EMO:neutral|happy|frustrated|thinking] 或 [情感=中性|高兴|沮丧|思考] [SPEED:normal|fast|slow] / [SPEED:0.8x] 或 [语速=正常|快|慢] [STYLE:formal|casual] 或 [风格=正式|轻松] 2) 内联标记（一次性事件，插入停顿 / 填充音 / 非语言音，或临时改变状态） [THINKING] 思考停顿 + 迟疑语气（=情绪思考/慢速/正式，并插入停顿） [SEARCHING] 搜索性停顿（同上，停顿略短） [PAUSE] / / [停顿] 插入停顿 [BREATH] / Fish S1 原生吸气声 [SIGH] / Fish S1 原生叹气声 [LAUGH:small] / [LAUGH] / Fish S1 原生轻笑声 ... / [强调]...[/强调] 对包裹的文本加重强调 非语言片段会保留为 S1 的 `(gasping)` / `(sighing)` / `(chuckling)` 原生标记， 由 Fish Audio 直接合成声音，而不是把拟声文字念出来。 """ import re # 中文取值 -> 英文维度值的别名映射 _EMO_ALIAS = { "中性": "neutral", "高兴": "happy", "开心": "happy", "兴奋": "happy", "沮丧": "frustrated", "无奈": "frustrated", "思考": "thinking", } _SPEED_ALIAS = {"正常": "normal", "快": "fast", "快速": "fast", "慢": "slow", "慢速": "slow"} _STYLE_ALIAS = {"正式": "formal", "轻松": "casual", "随意": "casual"} # 各内联事件插入的停顿时长（毫秒） PAUSE_MS = 500 BREATH_MS = 400 THINKING_MS = 1200 SEARCHING_MS = 700 SIGH_TAIL_MS = 300 def _norm(value: str, alias: dict) -> str: v = value.strip() return alias.get(v, v.lower()) class Segment(dict): """一个片段：type='speech'(text, emotion, speed, style, emphasis) 或 type='silence'(ms)。""" def parse(text: str, trace: list | None = None): """ 解析带控制标记的文本，返回片段列表。 若传入 trace（list），会把「标记 -> 动作」的解析过程逐条记入，便于打印。 """ def log(msg): if trace is not None: trace.append(msg) # 当前状态（状态标记会持续改变它） state = {"emotion": "neutral", "speed": "normal", "style": "formal", "emphasis": False} segments: list[Segment] = [] buf = [] # 累积当前状态下的普通文本 def flush(): """把缓冲区的普通文本作为一个 speech 片段输出。""" s = "".join(buf).strip() buf.clear() if s: segments.append(Segment(type="speech", text=s, **state)) def add_silence(ms, why): flush() segments.append(Segment(type="silence", ms=ms)) log(f" {why:22s} -> 插入静音 {ms}ms") def add_speech_token(token, emotion, speed, style, why): """Insert a Fish S1 native non-verbal marker as a speech segment.""" flush() segments.append(Segment(type="speech", text=token, emotion=emotion, speed=speed, style=style, emphasis=False)) log(f" {why:22s} -> Fish S1 原生标记 '{token}' (情绪={emotion},语速={speed})") def set_state(**kw): flush() # 状态改变前，先把旧状态的文本收尾 for k, v in kw.items(): state[k] = v # 用一个总正则切出所有 [..] 与 <..> 标记，其余为普通文本 parts = re.split(r"(\[[^\]]*\]|<[^>]+>)", text) for part in parts: if not part: continue if not re.fullmatch(r"\[[^\]]*\]|<[^>]+>", part): buf.append(part) # 普通文本 continue m = part # 标记原文 inner = m[1:-1].strip() # --- 状态标记：EMO / SPEED / STYLE（英文冒号式 或 中文等号式） --- km = re.match(r"(?i)^(EMO|SPEED|STYLE)\s*:\s*(.+)$", inner) cm = re.match(r"^(情感|语速|风格)\s*=\s*(.+)$", inner) if km: key, val = km.group(1).upper(), km.group(2) elif cm: key = {"情感": "EMO", "语速": "SPEED", "风格": "STYLE"}[cm.group(1)] val = cm.group(2) else: key = val = None if key == "EMO": e = _norm(val, _EMO_ALIAS) set_state(emotion=e) log(f" {m:22s} -> 情绪 = {e}") continue if key == "SPEED": raw = val.strip() v = raw.lower().replace("x", "") # 兼容 0.8x # 先认英文取值(normal/fast/slow)，再认中文别名(正常/快/慢) if v in ("normal", "fast", "slow"): s = v elif raw in _SPEED_ALIAS: s = _SPEED_ALIAS[raw] else: # 数字型（如 0.8）就近映射到 fast/slow/normal，仅用于展示 try: f = float(v) s = "fast" if f > 1.05 else ("slow" if f < 0.95 else "normal") except ValueError: s = "normal" set_state(speed=s) log(f" {m:22s} -> 语速 = {s}") continue if key == "STYLE": st = _norm(val, _STYLE_ALIAS) set_state(style=st) log(f" {m:22s} -> 风格 = {st}") continue # --- 强调包裹 --- low = inner.lower() if low in ("emphasis", "强调"): set_state(emphasis=True) log(f" {m:22s} -> 开启强调") continue if low in ("/emphasis", "/强调"): set_state(emphasis=False) log(f" {m:22s} -> 关闭强调") continue # --- 内联事件标记 --- tag = low.split(":")[0] # laugh:small -> laugh if tag == "thinking": set_state(emotion="thinking", speed="slow", style="formal") log(f" {m:22s} -> 切换到 思考/慢速/正式 参考语音") add_silence(THINKING_MS, "[THINKING] 停顿") add_speech_token("(uncertain)嗯……", "thinking", "slow", "formal", "[THINKING] 填充音") continue if tag == "searching": set_state(emotion="thinking", speed="slow", style="formal") log(f" {m:22s} -> 切换到 思考/慢速/正式 参考语音") add_silence(SEARCHING_MS, "[SEARCHING] 停顿") add_speech_token("(uncertain)那个……", "thinking", "slow", "formal", "[SEARCHING] 填充音") continue if tag in ("pause", "停顿"): add_silence(PAUSE_MS, m) continue if tag in ("breath", "换气"): add_speech_token("(gasping)", state["emotion"], state["speed"], state["style"], m) continue if tag == "sigh": add_speech_token("(sighing)", "frustrated", "slow", "formal", m) segments.append(Segment(type="silence", ms=SIGH_TAIL_MS)) continue if tag == "laugh": add_speech_token("(chuckling)", "happy", "fast", "casual", m) continue # 未知标记：忽略但记录 log(f" {m:22s} -> [未知标记，已忽略]") flush() return segments # --------------------------------------------------------------------------- # 控制标记 -> 动作 的静态映射表（离线可查，供 demo.py --dump-mapping 打印） # 这是「书中控制标记 -> 参考语音 / 非语言音」映射关系的单一事实来源。 # --------------------------------------------------------------------------- # (类别, 标记写法, 中文写法, 映射到的动作) MARKER_REFERENCE = [ ("状态", "[EMO:neutral|happy|frustrated|thinking]", "[情感=中性|高兴|沮丧|思考]", "切换情绪维度，选择参考语音"), ("状态", "[SPEED:normal|fast|slow] / [SPEED:0.8x]", "[语速=正常|快|慢]", "切换语速维度（数字型就近映射到 fast/slow/normal）"), ("状态", "[STYLE:formal|casual]", "[风格=正式|轻松]", "切换口吻维度"), ("内联", "[THINKING]", "—", "切到「思考/慢速/正式」参考语音 + 插入 500ms 停顿"), ("内联", "[SEARCHING]", "—", "切到「思考/慢速/正式」参考语音 + 插入 400ms 停顿"), ("内联", "[PAUSE] / ", "[停顿]", "插入 500ms 静音"), ("内联", "[BREATH] / ", "[换气]", "插入 400ms 换气停顿"), ("内联", "[SIGH] / ", "—", "叹气拟声词「唉——」(沮丧音色) + 300ms 停顿"), ("内联", "[LAUGH:small] / [LAUGH] / ", "—", "轻笑拟声词「哈哈，」(高兴音色)"), ("内联", "…", "[强调]…[/强调]", "对包裹文本追加「加重强调」提示词"), ] def format_marker_reference() -> str: """把 MARKER_REFERENCE 渲染成可打印的对齐表格字符串。""" lines = [f"{'类别':<4} {'标记写法':<40} {'中文写法':<24} 动作", "-" * 100] for cat, mark, zh, action in MARKER_REFERENCE: lines.append(f"{cat:<4} {mark:<40} {zh:<24} {action}") return "\n".join(lines) if __name__ == "__main__": print("控制标记 -> 动作 映射表：\n") print(format_marker_reference())