328 lines
12 KiB
Python
328 lines
12 KiB
Python
#!/usr/bin/env python3
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"""
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《林夏》TTS 批量生产脚本
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用法:
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conda activate cosyvoice
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cd /home/xsl/blind
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python audio/batch_tts.py [--role mom] [--test]
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参数:
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--role ROLE 只生产指定角色（不指定则全部）
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--test 只合成第一条，用于快速验证环境
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--dry-run 只打印任务列表，不实际合成
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"""
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import os, sys, time, argparse, warnings
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import torch
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import soundfile as sf # torchaudio nightly requires torchcodec; use soundfile instead
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warnings.filterwarnings("ignore")
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COSYVOICE_DIR = "/home/xsl/tools/CosyVoice"
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PROJECT_DIR = "/home/xsl/blind"
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REF_DIR = f"{PROJECT_DIR}/audio/00_raw/tts/prompt_ref"
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OUT_DIR = f"{PROJECT_DIR}/audio/00_raw/tts"
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sys.path.insert(0, COSYVOICE_DIR)
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sys.path.insert(0, f"{COSYVOICE_DIR}/third_party/Matcha-TTS")
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os.chdir(COSYVOICE_DIR)
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# ──────────────────────────────────────────────────────────────
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# 角色配置（对应 SOP §4.2）
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# ref_wav / ref_text 在参考音频备齐前先留空
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# ──────────────────────────────────────────────────────────────
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ROLES = {
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"mom": {
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"speed": 0.92,
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"ref_wav": f"{REF_DIR}/mom_ref.wav",
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"ref_text": "", # ← 参考音频对应文字，备齐后填入
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},
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"azhe": {
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"speed": 1.05,
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"ref_wav": f"{REF_DIR}/azhe_ref.wav",
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"ref_text": "",
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},
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"xiaomei": {
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"speed": 1.10,
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"ref_wav": f"{REF_DIR}/xiaomei_ref.wav",
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"ref_text": "",
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},
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"xiaomei_drunk": { # 醉语音用同参考，speed 调慢
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"speed": 0.95,
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"ref_wav": f"{REF_DIR}/xiaomei_ref.wav",
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"ref_text": "",
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},
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"zhounan": {
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"speed": 0.95,
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"ref_wav": f"{REF_DIR}/zhounan_ref.wav",
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"ref_text": "",
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},
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"hr": {
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"speed": 1.00,
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"ref_wav": f"{REF_DIR}/hr_ref.wav",
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"ref_text": "",
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},
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"anan": {
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"speed": 1.15,
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"ref_wav": f"{REF_DIR}/anan_ref.wav",
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"ref_text": "",
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},
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"dorm_a": {
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"speed": 1.10,
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"ref_wav": f"{REF_DIR}/dorm_a_ref.wav",
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"ref_text": "",
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},
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"dorm_b": {
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"speed": 1.00,
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"ref_wav": f"{REF_DIR}/dorm_b_ref.wav",
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"ref_text": "",
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},
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"dorm_c": {
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"speed": 0.95,
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"ref_wav": f"{REF_DIR}/dorm_c_ref.wav",
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"ref_text": "",
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},
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"delivery": {
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"speed": 1.20,
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"ref_wav": f"{REF_DIR}/delivery_ref.wav",
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"ref_text": "",
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},
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"self_3y": { # 复用 xiaomei，speed +0.05
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"speed": 1.15,
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"ref_wav": f"{REF_DIR}/xiaomei_ref.wav",
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"ref_text": "",
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},
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# system 用预训练音色，不在这里
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}
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# ──────────────────────────────────────────────────────────────
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# 台词表（对应林夏.md §3 + §5）
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# 格式: (输出文件前缀, 角色key, 台词)
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# 长戏（≥30s）已按 SOP §5.3 拆分为分段
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# ──────────────────────────────────────────────────────────────
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LINES = [
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# ── 01 · 21:03 妈妈电话 ──
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("lv11_2103_mom_call_01",
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"mom",
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"今晚煮了你爱吃的排骨，给你拍张照啊。下周五回来一趟，你高中物理老师的儿子，挺好的。"),
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# ── 02 · 21:15 小美三连 ──
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("lv11_2115_xiaomei_voice_01", "xiaomei", "在吗"),
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("lv11_2115_xiaomei_voice_02", "xiaomei", "你被甩了我都听说了"),
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("lv11_2115_xiaomei_voice_03", "xiaomei", "明天晚上喝酒，海底捞旁边那家，不许放鸽子"),
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# ── 03 · 21:20 外卖小哥 ──
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("lv11_2120_delivery_call_01",
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"delivery",
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"你好你的麻辣烫到了，放门口可以吗？"),
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# ── 04 · 21:30 阿哲语音 ──
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("lv11_2130_azhe_voice_01",
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"azhe",
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"嗯……夏夏。我那个AirPods充电盒，好像落你抽屉里了。"
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"你方便的时候帮我寄一下吗，工位还要用。地址我等下发你。"),
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# ── 05 · 21:45 HR 王姐 ──
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("lv11_2145_hr_voice_01",
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"hr",
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"夏夏啊，离职流程你下周三之前办完哈，公积金那边记得跟进。"
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"辛苦啦，外面有合适的工作我帮你留意。"),
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# ── 06 · 22:00 安安 ──
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("lv11_2200_anan_voice_01",
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"anan",
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"夏夏！我在helens！要不要过来！我请客！"),
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# ── 07 · 22:15 寝室群 ──
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("lv11_2215_dorm_a_voice_01", "dorm_a", "哎你们看，我今天升职了！"),
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("lv11_2215_dorm_b_voice_01", "dorm_b", "真的啊！恭喜恭喜！太厉害了！"),
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("lv11_2215_dorm_c_voice_01", "dorm_c", "厉害！那要请客啊！"),
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("lv11_2215_dorm_a_voice_02", "dorm_a", "哈哈哈必须的！夏夏你怎么不说话呀"),
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("lv11_2215_dorm_b_voice_02", "dorm_b", "夏夏在忙吧，别打扰她了"),
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# ── 09 · 22:45 小美醉语音（分 4 段）──
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("lv11_2245_xiaomei_voice_01_seg1",
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"xiaomei_drunk",
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"夏夏夏夏夏。你睡了吗？我跟你说，我跟你说啊……今天我喝多了……"),
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("lv11_2245_xiaomei_voice_01_seg2",
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"xiaomei_drunk",
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"你别嫌我烦哈，我跟你说……其实啊……阿哲他，大三那年，他来追过我。"
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"我没答应他。我那时候就觉得他这人，呵，差点意思。"),
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("lv11_2245_xiaomei_voice_01_seg3",
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"xiaomei_drunk",
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"你跟他在一起的时候，我没说，因为说了也没意义嘛对吧。"
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"现在他甩了你，我才敢说。"),
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("lv11_2245_xiaomei_voice_01_seg4",
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"xiaomei_drunk",
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"夏夏，你听到了吗？你别恨我啊。……喂？算了。"),
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# ── 10 · 23:00 妈妈文字 ──
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("lv11_2300_mom_text_01", "mom", "睡了吗？"),
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# ── 11 · 23:15 阿哲电话 ──
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("lv11_2315_azhe_call_01", "azhe", "我能过去拿吗？就5分钟"),
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# ── 12 · 23:30 周南第一条 ──
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("lv11_2330_zhounan_voice_01",
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"zhounan",
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"林夏，是我，周南。你应该不记得我了吧，初三坐你后桌那个"),
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# ── 13 · 23:45 周南长讲述（4 段）──
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("lv11_2345_zhounan_voice_01",
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"zhounan",
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"其实我一直想找机会跟你说声谢谢。初三那年你借我笔记，那次考试我才没挂科。"),
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("lv11_2345_zhounan_voice_02",
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"zhounan",
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"后来高考，我没考好。复读了一年，去了一个二本。然后就回老家了，没什么好说的。"),
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("lv11_2345_zhounan_voice_03",
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"zhounan",
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"今年第一次来北京出差。来之前我想着，要不要找你。找了很久，才在一个校友群里看到你。"
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"你现在过得怎么样？"),
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("lv11_2345_zhounan_voice_04",
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"zhounan",
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"今天我生日。本来就想跟你说一声，对不起这么晚。"),
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# ── 14 · 00:15 妈妈电话 ──
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("lv11_0015_mom_call_01",
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"mom",
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"夏夏，你不接电话我有点担心。妈妈知道你工作忙，你早点睡。"),
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# ── 16 · 02:00 妈妈长语音（分 8 段）──
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("lv11_0200_mom_voice_01_seg1",
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"mom",
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"夏夏。妈妈知道你今天电话不接。妈妈不催你，就是想跟你说一件事。"),
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("lv11_0200_mom_voice_01_seg2",
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"mom",
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"你24了对吧。妈妈24那年——你应该没听我说过——"),
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("lv11_0200_mom_voice_01_seg3",
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"mom",
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"那时候妈妈在广州，给一个香港老板做秘书，1995年。"
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"那年我也被分手过。也被开除过。一模一样的春天。"),
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("lv11_0200_mom_voice_01_seg4",
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"mom",
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"那年我哭得特别难看。后来呢？后来就没什么后来了。"
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"我回了老家，认识了你爸，生了你。"),
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("lv11_0200_mom_voice_01_seg5",
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"mom",
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"我跟你说这个不是想跟你说什么都会过去——"
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"我想跟你说，那年夏天我没死，是因为我外婆每天晚上都给我打一个电话。"),
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("lv11_0200_mom_voice_01_seg6",
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"mom",
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"她不说什么，就问我今天吃饭了没。"),
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("lv11_0200_mom_voice_01_seg7",
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"mom",
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"我现在打给你，你不接也没事。妈妈给你发个语音，你什么时候想听就听。你不用回我。"),
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("lv11_0200_mom_voice_01_seg8",
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"mom",
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"你今天接了好多电话吧。妈妈不打扰你了。晚安。"),
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# ── self-3y 三版（台词待编剧定稿）──
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# ("lv11_0030_self-3y_voice_01", "self_3y", "（明朗版台词）"),
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# ("lv11_0030_self-3y_voice_02", "self_3y", "（迷茫版台词）"),
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# ("lv11_0030_self-3y_voice_03", "self_3y", "（温柔版台词）"),
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]
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def load_model():
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from cosyvoice.cli.cosyvoice import CosyVoice2
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print("加载 CosyVoice2 模型...")
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model = CosyVoice2("pretrained_models/CosyVoice2-0.5B")
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print(f"模型就绪，采样率 {model.sample_rate}Hz")
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return model
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def load_ref(role_cfg):
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from cosyvoice.utils.file_utils import load_wav
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wav_path = role_cfg["ref_wav"]
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if not os.path.exists(wav_path):
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return None, None
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wav = load_wav(wav_path, 16000)
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# 裁到 30s 以内
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max_samples = 16000 * 30
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if wav.shape[1] > max_samples:
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wav = wav[:, :max_samples]
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return wav, role_cfg["ref_text"]
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def synthesize(model, filename, role_key, text):
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role_cfg = ROLES[role_key]
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ref_wav, ref_text = load_ref(role_cfg)
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out_path = f"{OUT_DIR}/{filename}_v1.wav"
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if os.path.exists(out_path):
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print(f" [跳过，已存在] {filename}")
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return True
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if ref_wav is None:
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print(f" [跳过，缺参考音频] {role_key}: {role_cfg['ref_wav']}")
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return False
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if not ref_text.strip():
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print(f" [跳过，ref_text 未填] {role_key}")
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return False
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t0 = time.time()
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chunks = []
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for chunk in model.inference_zero_shot(
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tts_text=text,
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prompt_text=ref_text,
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prompt_speech_16k=ref_wav,
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stream=False,
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speed=role_cfg["speed"],
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):
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chunks.append(chunk["tts_speech"])
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if not chunks:
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print(f" [失败，无输出] {filename}")
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return False
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audio = torch.concat(chunks, dim=1)
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duration = audio.shape[1] / model.sample_rate
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sf.write(out_path, audio.squeeze().cpu().numpy(), model.sample_rate)
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elapsed = time.time() - t0
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rtf = elapsed / duration if duration > 0 else 0
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print(f" ✓ {filename} {duration:.1f}s 音频 {elapsed:.1f}s 耗时 RTF={rtf:.3f}")
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return True
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument("--role", help="只合成指定角色")
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parser.add_argument("--test", action="store_true", help="只合成第一条")
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parser.add_argument("--dry-run", action="store_true", help="只打印任务")
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args = parser.parse_args()
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lines = LINES
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if args.role:
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lines = [(f, r, t) for f, r, t in lines if r == args.role or r.startswith(args.role)]
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if args.test:
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lines = lines[:1]
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print(f"\n{'='*60}")
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print(f" 《林夏》TTS 批量合成 共 {len(lines)} 条")
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print(f"{'='*60}")
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if args.dry_run:
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for f, r, t in lines:
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ref_exists = "✓" if os.path.exists(ROLES.get(r, {}).get("ref_wav", "")) else "✗缺参考"
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print(f" [{ref_exists}] {f} [{r}] {t[:30]}...")
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return
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model = load_model()
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ok, skip, fail = 0, 0, 0
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for i, (filename, role_key, text) in enumerate(lines, 1):
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print(f"\n[{i}/{len(lines)}] {filename}")
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result = synthesize(model, filename, role_key, text)
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if result is True: ok += 1
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elif result is None: skip += 1
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else: fail += 1
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print(f"\n{'='*60}")
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print(f" 完成：{ok} 条 跳过：{skip} 条 失败：{fail} 条")
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print(f" 输出目录：{OUT_DIR}")
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print(f"{'='*60}\n")
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if __name__ == "__main__":
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main()
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