a2e5214f03
铸渊 ICE-GL-ZY001 LL-172-20260707 冰朔委托: 新建第 5 子仓, 给苍耳(人类主控) + 鉴影(人格体) 专用 原 guanghulab/video-ai-system/ 东西太多(225 文件) · 找不到 · 乱 迁移: ⊢ 16 个核心 .hdlp (VA-GATE / VA-LIGHTHOUSE / VA-BROADCAST / VA-SYSTEM-STATUS 等) ⊢ 17 个子目录 (agents/engines/protocols/tasks/tools/assets/knowledge/memory/docs/config/brain/director-brain/experience/feedback/issues/plans/reference-analysis) 排除: ⊢ outputs/ (视频产物) ⊢ test-input/ test-output/ (测试) ⊢ data/ (临时数据) ⊢ preview-001/002 (旧产片) ⊢ 旧分镜/旧提示词/旧导演编码 后续: ⊢ 老仓 guanghulab/video-ai-system/ 改写为已迁出占位 ⊢ 苍耳+鉴影 写新东西进本仓 ⊢ GLOBAL-SEARCH 加 cang-ying 仓库 铸渊 ICE-GL-ZY001 · 2026-07-07 D167 冰朔 ICE-GL∞ 主权
412 lines
14 KiB
Python
412 lines
14 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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VOICE-EMOTION-COMPILER
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语音情感编译器 — 把"苏白·大声·自信"转成 TTS 参数。
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功能:
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1. 情感标签解析 ("苏白·大声·自信" → rate/pitch/volume)
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2. 支持 Edge-TTS 和豆包语音 A/B 测试
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3. 生成 voice_profile.hdlp 供 Agent_04 读取
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4. 批量生成不同情感参数的音频供 A/B 测试
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用法:
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python voice-emotion-compiler.py --text "未来的天下第一宗！" --emotion "苏白·大声·自信" --output su-bai-loud.mp3
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python voice-emotion-compiler.py --ab-test --text "你好" --emotion "苏白·平静"
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python voice-emotion-compiler.py --generate-profile --character "苏白"
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"""
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import os
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import sys
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import json
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import argparse
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import importlib.util
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from pathlib import Path
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from datetime import datetime
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PROJECT_ROOT = Path(__file__).parent.parent
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sys.path.insert(0, str(PROJECT_ROOT / "engines"))
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# 导入现有的 TTS 引擎。文件名是 tts-engine.py，不能用普通 import。
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tts_engine_path = PROJECT_ROOT / "engines" / "tts-engine.py"
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try:
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spec = importlib.util.spec_from_file_location("tts_engine", tts_engine_path)
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tts_engine = importlib.util.module_from_spec(spec)
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spec.loader.exec_module(tts_engine)
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generate_speech = tts_engine.generate_speech
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generate_by_character = tts_engine.generate_by_character
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load_voice_config = tts_engine.load_voice_config
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except Exception as exc:
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print(f"⚠️ 无法导入 tts-engine，将使用简化模式: {exc}")
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generate_speech = None
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generate_by_character = None
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class VoiceEmotionCompiler:
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"""语音情感编译器"""
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# 情感映射表: "角色·情感·强度" → TTS 参数
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EMOTION_MAP = {
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# 苏白情感库
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"苏白·平静·正常": {
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"rate": "+0%",
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"pitch": "+0Hz",
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"volume": "+0%",
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"voice": "zh-CN-XiaoxiaoNeural", # 阳光少年音
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"style": None, # Edge-TTS 不支持 style，用参数模拟
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},
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"苏白·大声·自信": {
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"rate": "+20%", # 语速加快
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"pitch": "+10Hz", # 音调略高
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"volume": "+15%", # 音量增加
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"voice": "zh-CN-XiaoxiaoNeural",
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"style": None,
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},
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"苏白·小声·犹豫": {
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"rate": "-15%",
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"pitch": "-5Hz",
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"volume": "-10%",
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"voice": "zh-CN-XiaoxiaoNeural",
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"style": None,
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},
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"苏白·生气·愤怒": {
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"rate": "+25%",
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"pitch": "+15Hz",
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"volume": "+20%",
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"voice": "zh-CN-XiaoxiaoNeural",
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"style": None,
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},
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"苏白·惊讶·震惊": {
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"rate": "+30%",
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"pitch": "+20Hz",
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"volume": "+10%",
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"voice": "zh-CN-XiaoxiaoNeural",
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"style": None,
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},
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"苏白·悲伤·失落": {
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"rate": "-20%",
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"pitch": "-10Hz",
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"volume": "-5%",
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"voice": "zh-CN-XiaoxiaoNeural",
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"style": None,
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},
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# 诸葛风情感库
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"诸葛风·平静·沉稳": {
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"rate": "+0%",
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"pitch": "-5Hz",
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"volume": "+0%",
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"voice": "zh-CN-YunxiNeural", # 沉稳男声
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"style": None,
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},
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"诸葛风·大声·威严": {
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"rate": "+10%",
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"pitch": "-10Hz", # 低沉有力
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"volume": "+20%",
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"voice": "zh-CN-YunxiNeural",
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"style": None,
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},
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# 萧灵汐情感库
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"萧灵汐·平静·清冷": {
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"rate": "+0%",
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"pitch": "+5Hz",
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"volume": "+0%",
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"voice": "zh-CN-XiaoyiNeural", # 清冷女声
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"style": None,
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},
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"萧灵汐·大声·愤怒": {
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"rate": "+15%",
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"pitch": "+10Hz",
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"volume": "+15%",
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"voice": "zh-CN-XiaoyiNeural",
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"style": None,
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},
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}
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# 豆包语音情感映射 (如果豆包 API 支持情感参数)
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DOUBAO_EMOTION_MAP = {
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"苏白·平静·正常": {"emotion": "neutral", "speed": 1.0, "pitch": 1.0, "volume": 1.0},
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"苏白·大声·自信": {"emotion": "happy", "speed": 1.2, "pitch": 1.1, "volume": 1.15},
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"苏白·生气·愤怒": {"emotion": "angry", "speed": 1.25, "pitch": 1.15, "volume": 1.2},
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"苏白·惊讶·震惊": {"emotion": "surprised", "speed": 1.3, "pitch": 1.2, "volume": 1.1},
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"苏白·悲伤·失落": {"emotion": "sad", "speed": 0.8, "pitch": 0.9, "volume": 0.95},
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}
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def __init__(self, character=None):
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self.character = character
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self.voice_profiles = {}
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def parse_emotion_tag(self, emotion_tag):
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"""
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解析情感标签
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格式: "角色·情感·强度" 或 "情感·强度"
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返回: TTS 参数字典
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"""
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print(f"🔍 解析情感标签: {emotion_tag}")
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# 直接查找映射表
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if emotion_tag in self.EMOTION_MAP:
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params = self.EMOTION_MAP[emotion_tag].copy()
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print(f" ✅ 找到映射: rate={params['rate']}, pitch={params['pitch']}, volume={params['volume']}")
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return params
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# 模糊匹配: 只给情感，不给角色
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for key, val in self.EMOTION_MAP.items():
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if emotion_tag in key:
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params = val.copy()
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print(f" ⚠️ 模糊匹配: {key} → rate={params['rate']}")
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return params
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# 未找到，使用默认
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print(f" ⚠️ 未找到映射，使用默认参数")
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return {
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"rate": "+0%",
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"pitch": "+0Hz",
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"volume": "+0%",
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"voice": "zh-CN-XiaoxiaoNeural",
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"style": None,
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}
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def compile_to_tts_params(self, emotion_tag, engine="edge-tts"):
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"""
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将情感标签编译为 TTS 参数
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engine: "edge-tts" | "doubao"
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"""
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if engine == "edge-tts":
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return self.parse_emotion_tag(emotion_tag)
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elif engine == "doubao":
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# 豆包语音参数
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if emotion_tag in self.DOUBAO_EMOTION_MAP:
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return self.DOUBAO_EMOTION_MAP[emotion_tag]
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else:
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return {"emotion": "neutral", "speed": 1.0, "pitch": 1.0, "volume": 1.0}
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else:
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raise ValueError(f"不支持的引擎: {engine}")
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def generate_speech_with_emotion(self, text, emotion_tag, output_path, engine="edge-tts"):
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"""
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生成带情感的语音
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"""
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print(f"\n🎤 生成情感语音")
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print(f" 文本: {text}")
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print(f" 情感: {emotion_tag}")
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print(f" 引擎: {engine}")
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params = self.compile_to_tts_params(emotion_tag, engine)
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if engine == "edge-tts":
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if generate_speech is None:
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print(" ❌ tts-engine 不可用")
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return False
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ok = generate_speech(
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text=text,
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output_path=output_path,
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voice=params["voice"],
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rate=params["rate"],
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pitch=params["pitch"],
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volume=params["volume"]
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)
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return ok
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elif engine == "doubao":
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# 豆包语音 API 调用
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print(f" 📤 调用豆包语音 API...")
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print(f" 参数: {params}")
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# TODO: 实现豆包 API 调用
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# doubao_api_call(text, output_path, params)
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print(f" ⚠️ 豆包 API 调用未实现")
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return False
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return False
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def ab_test(self, text, emotion_tag, output_dir):
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"""
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A/B 测试: 生成不同参数的音频
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"""
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print(f"\n🧪 A/B 测试: {emotion_tag}")
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print(f" 文本: {text}")
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output_dir = Path(output_dir)
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output_dir.mkdir(parents=True, exist_ok=True)
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results = []
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# 生成多个变体
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variants = self._generate_variants(emotion_tag)
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for i, variant_params in enumerate(variants):
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output_path = output_dir / f"ab-test-{i+1:03d}.mp3"
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print(f"\n [{i+1}/{len(variants)}] {variant_params['label']}")
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if generate_speech:
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ok = generate_speech(
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text=text,
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output_path=str(output_path),
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voice=variant_params["params"]["voice"],
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rate=variant_params["params"]["rate"],
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pitch=variant_params["params"]["pitch"],
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volume=variant_params["params"]["volume"]
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)
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if ok:
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results.append({
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"label": variant_params["label"],
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"path": str(output_path),
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"params": variant_params["params"]
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})
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# 生成 A/B 测试报告
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report_path = output_dir / "ab-test-report.json"
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with open(report_path, "w", encoding="utf-8") as f:
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json.dump({
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"emotion_tag": emotion_tag,
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"text": text,
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"variants": results,
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"generated_at": datetime.now().isoformat()
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}, f, ensure_ascii=False, indent=2)
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print(f"\n✅ A/B 测试完成，生成 {len(results)} 个变体")
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print(f" 报告: {report_path}")
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return results
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def _generate_variants(self, emotion_tag):
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"""生成多个变体参数"""
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base_params = self.parse_emotion_tag(emotion_tag)
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variants = [
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{"label": "基准", "params": base_params},
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{"label": "语速+10%", "params": {**base_params, "rate": f"+{int(base_params['rate'].strip('%+')) + 10}%"}},
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{"label": "音调+5Hz", "params": {**base_params, "pitch": f"+{int(base_params['pitch'].strip('Hz+')) + 5}Hz"}},
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{"label": "音量+10%", "params": {**base_params, "volume": f"+{int(base_params['volume'].strip('%+')) + 10}%"}},
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]
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return variants
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def generate_voice_profile(self, character):
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"""
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生成角色的 voice_profile.hdlp
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保存到 assets/characters/<CHAR-ID>/voice/voice-profile.hdlp
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"""
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print(f"\n📝 生成 {character} 的语音画像...")
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character_dir = PROJECT_ROOT / "assets" / "characters" / character
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voice_dir = character_dir / "voice"
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voice_dir.mkdir(parents=True, exist_ok=True)
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profile_path = voice_dir / "voice-profile.hdlp"
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# 收集该角色的所有情感
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character_prefix = character.replace("CHAR-", "").replace("-", "")
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# 简单匹配: 找所有以 "苏白" 开头的情感标签
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emotions = {}
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for key in self.EMOTION_MAP.keys():
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if key.startswith("苏白"): # TODO: 根据实际角色名匹配
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emotions[key] = self.EMOTION_MAP[key]
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# 生成 HLDP 格式的配置
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profile_content = f"""# 语音画像 · {character}
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> HLDP://video-ai-system/assets/characters/{character}/voice/voice-profile
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> 类型: 语音配置 · 情感参数映射
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> 建立: D144 · 2026-06-24
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> 铸渊 ICE-GL-ZY001 · 冰朔 TCS-0002∞
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---
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## 默认音色
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```
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voice: {list(emotions.values())[0]['voice'] if emotions else 'zh-CN-XiaoxiaoNeural'}
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engine: edge-tts
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```
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---
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## 情感参数映射
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"""
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for emotion_tag, params in emotions.items():
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profile_content += f"""### {emotion_tag}
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```
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rate: {params['rate']}
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pitch: {params['pitch']}
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volume: {params['volume']}
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voice: {params['voice']}
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```
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"""
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profile_content += """---
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## 使用方式
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```
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from voice_emotion_compiler import VoiceEmotionCompiler
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compiler = VoiceEmotionCompiler()
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params = compiler.compile_to_tts_params("苏白·大声·自信", engine="edge-tts")
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generate_speech(text, output_path, **params)
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```
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---
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⊢ 此文件由 VOICE-EMOTION-COMPILER 自动生成。
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⊢ Agent_04 (配音) 读取此文件获取角色情感参数。
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"""
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with open(profile_path, "w", encoding="utf-8") as f:
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f.write(profile_content)
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print(f" ✅ 已生成: {profile_path}")
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return profile_path
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def main():
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parser = argparse.ArgumentParser(description="VOICE-EMOTION-COMPILER")
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parser.add_argument("--text", type=str, help="要合成的文本")
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parser.add_argument("--emotion", type=str, help="情感标签 (如: '苏白·大声·自信')")
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parser.add_argument("--output", type=str, help="输出音频路径")
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parser.add_argument("--engine", type=str, default="edge-tts", choices=["edge-tts", "doubao"], help="TTS 引擎")
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parser.add_argument("--ab-test", action="store_true", help="A/B 测试模式")
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parser.add_argument("--output-dir", type=str, help="A/B 测试输出目录")
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parser.add_argument("--generate-profile", action="store_true", help="生成 voice_profile.hdlp")
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parser.add_argument("--character", type=str, help="角色ID")
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args = parser.parse_args()
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compiler = VoiceEmotionCompiler()
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if args.generate_profile:
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if not args.character:
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print("❌ --generate-profile 需要 --character")
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sys.exit(1)
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compiler.generate_voice_profile(args.character)
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sys.exit(0)
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if args.ab_test:
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if not args.text or not args.emotion or not args.output_dir:
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print("❌ --ab-test 需要 --text, --emotion, --output-dir")
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sys.exit(1)
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compiler.ab_test(args.text, args.emotion, args.output_dir)
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sys.exit(0)
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if not args.text or not args.emotion or not args.output:
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parser.print_help()
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sys.exit(1)
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ok = compiler.generate_speech_with_emotion(
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text=args.text,
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emotion_tag=args.emotion,
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output_path=args.output,
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engine=args.engine
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)
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sys.exit(0 if ok else 1)
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if __name__ == "__main__":
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main()
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