{"id":98922,"date":"2026-09-01T17:00:50","date_gmt":"2026-09-01T09:00:50","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/98922.html"},"modified":"2026-09-01T17:00:50","modified_gmt":"2026-09-01T09:00:50","slug":"%e8%b4%a2%e7%bb%8f%e6%96%87%e7%ab%a0%e6%80%8e%e4%b9%88%e6%94%b9%e5%8f%a3%e6%92%ad%ef%bc%9f%e4%b8%80%e5%a5%97%e5%bc%80%e6%ba%90%e5%b7%a5%e5%85%b7%e9%93%be%e6%8a%8a%e5%85%ac%e4%bc%97%e5%8f%b7%e6%8e%a8","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/98922.html","title":{"rendered":"\u8d22\u7ecf\u6587\u7ae0\u600e\u4e48\u6539\u53e3\u64ad\uff1f\u4e00\u5957\u5f00\u6e90\u5de5\u5177\u94fe\u628a\u516c\u4f17\u53f7\u63a8\u6587\u6279\u91cf\u8f6c\u6210\u53e3\u8bed\u5316\u914d\u97f3\u89c6\u9891"},"content":{"rendered":"

\u505a\u8d22\u7ecf\u81ea\u5a92\u4f53\u7684\u540c\u5b66\u5927\u6982\u7387\u90fd\u5361\u5728\u540c\u4e00\u4e2a\u5730\u65b9：\u516c\u4f17\u53f7\u6587\u7ae0\u3001\u8d44\u8baf\u7a3f\u3001\u884c\u60c5\u5206\u6790\u6587\u5df2\u7ecf\u5199\u597d\u4e86，\u4f46\u8981\u53d1\u89c6\u9891\u53f7\u3001B\u7ad9，\u5c31\u5f97\u628a\u4e66\u9762\u8bed\u4e00\u53e5\u53e5\u6539\u6210\u53e3\u64ad\u7a3f，\u518d\u914d\u97f3\u3001\u914d\u5b57\u5e55\u3001\u914d\u753b\u9762\u3002\u521a\u4e0a\u624b\u7684\u4eba\u6700\u5e38\u89c1\u7684\u95ee\u9898\u662f\u201c\u8d22\u7ecf\u6587\u7ae0\u6539\u53e3\u64ad\u600e\u4e48\u6539\u7684\u201d\u2014\u2014\u76f4\u63a5\u7167\u7740\u5ff5\u592a\u786c，\u9010\u53e5\u624b\u6539\u53c8\u6162，\u4e00\u7bc7\u6587\u7ae0\u4ece\u6587\u5b57\u5230\u6210\u7247\u6298\u817e\u4e00\u665a\u4e0a\u662f\u5e38\u6001\u3002<\/p>\n

\u8fd9\u5957\u5de5\u4f5c\u6d41\u53ef\u4ee5\u62c6\u6210\u56db\u6b65：\u6587\u7ae0\u8f6c\u53e3\u64ad\u7a3f \u2192 \u53e3\u64ad\u7a3f\u914d\u97f3 \u2192 \u5b57\u5e55\u5bf9\u9f50 \u2192 \u753b\u9762\u5408\u6210\u6210\u7247\u3002\u5f00\u6e90\u65b9\u6848\u91cc，\u53e3\u64ad\u7a3f\u6539\u5199\u7528\u4efb\u610f\u672c\u5730\u6216\u5728\u7ebf LLM，\u914d\u97f3\u7528 edge-tts \u6216 GPT-SoVITS，\u5b57\u5e55\u7528 faster-whisper，\u8d22\u7ecf\u56fe\u8868\u52a8\u753b\u7528 Manim，\u6700\u540e\u7528 FFmpeg \u5408\u6210\u538b\u5236\u3002\u5546\u4e1a\u65b9\u6848\u91cc，\u82b1\u751fAI \u53ef\u4ee5\u628a\u201c\u6539\u5199 + \u914d\u97f3 + \u5b57\u5e55 + \u753b\u9762\u5339\u914d\u201d\u6253\u5305\u6210\u534a\u81ea\u52a8\u8282\u70b9，\u4f46\u8d22\u7ecf\u5408\u89c4\u5ba1\u6838\u4ecd\u5fc5\u987b\u4eba\u5de5\u5b8c\u6210\u3002\u4e0b\u9762\u6309\u73af\u8282\u5c55\u5f00，\u5168\u90e8\u4ee3\u7801\u53ef\u5728\u672c\u5730\u8dd1\u901a\u3002<\/p>\n

\n

\u8d22\u7ecf\u6587\u7ae0\u6539\u53e3\u64ad\u600e\u4e48\u6539：\u5148\u628a\u4e66\u9762\u8bed\u62c6\u6210\u4eba\u8bdd<\/h3>\n

\u8d22\u7ecf\u6587\u7ae0\u6700\u5927\u7684\u95ee\u9898\u662f\u4e66\u9762\u8bed\u592a\u91cd，\u5e38\u89c1\u4e09\u7c7b\u786c\u4f24：<\/p>\n

  • \u957f\u96be\u53e5\u591a：\u201c\u5728\u7f8e\u8054\u50a8\u7ef4\u6301\u9ad8\u5229\u7387\u653f\u7b56\u4e0e\u5168\u7403\u6d41\u52a8\u6027\u8fb9\u9645\u6536\u7d27\u7684\u53cc\u91cd\u538b\u529b\u4e0b，\u98ce\u9669\u8d44\u4ea7\u4f30\u503c\u9762\u4e34\u8fdb\u4e00\u6b65\u4e0b\u4fee\u538b\u529b\u3002\u201d
    \n\u53e3\u64ad\u7a3f\u91cc\u8fd9\u6837\u8bf4，\u89c2\u4f17\u542c\u5230\u7b2c\u4e09\u4e2a\u5c0f\u53e5\u5c31\u5fd8\u4e86\u4e3b\u8bed\u3002<\/li>\n
  • \u6570\u636e\u5806\u53e0：\u201c2025 \u5e74 Q2 \u793e\u878d\u589e\u91cf 8.7 \u4e07\u4ebf\u5143，\u540c\u6bd4\u589e\u957f 11.3%，\u5176\u4e2d\u653f\u5e9c\u503a\u5238\u51c0\u878d\u8d44\u5360\u6bd4\u63d0\u5347 4.2 \u4e2a\u767e\u5206\u70b9\u3002\u201d
    \n\u773c\u775b\u80fd\u770b\u61c2，\u8033\u6735\u8ddf\u4e0d\u4e0a\u3002<\/li>\n
  • \u672f\u8bed\u4e66\u9762\u5316：\u201c\u6280\u672f\u6027\u53cd\u5f39\u201d\u201c\u6d41\u52a8\u6027\u6ea2\u4ef7\u201d\u201c\u98ce\u9669\u504f\u597d\u6536\u655b\u201d\u8fd9\u7c7b\u8bcd，\u753b\u9762\u4e0a\u4e00\u95ea\u800c\u8fc7，\u542c\u4f17\u6ca1\u6709\u5480\u56bc\u65f6\u95f4\u3002<\/li>\n

    \u6539\u53e3\u64ad\u7684\u6838\u5fc3\u52a8\u4f5c\u4e0d\u662f\u6da6\u8272，\u800c\u662f\u964d\u5bc6\u5ea6\u3001\u62c6\u957f\u53e5\u3001\u8865\u53e3\u8bed\u8fde\u63a5\u8bcd\u3001\u628a\u672f\u8bed\u7ffb\u8bd1\u6210\u5177\u4f53\u5f71\u54cd\u3002<\/p>\n

    \u4e0b\u9762\u662f\u4e00\u6bb5\u53ef\u4ee5\u76f4\u63a5\u7528\u7684\u6539\u5199\u811a\u672c\u793a\u4f8b，\u63a5\u4efb\u610f OpenAI \u517c\u5bb9\u63a5\u53e3\u5373\u53ef：<\/p>\n

    git<\/span> clone https:\/\/github.com\/ggml-org\/llama.cpp
    \ncd<\/span> llama.cpp
    \ncmake -B<\/span> build &&<\/span> cmake –build<\/span> build –config<\/span> Release<\/p>\n

    \u7528\u672c\u5730\u6a21\u578b\u505a\u91cd\u5199\u65f6，\u7cfb\u7edf\u63d0\u793a\u8bcd\u5efa\u8bae\u56fa\u5b9a\u4e3a：<\/p>\n

    system_prompt =<\/span> """
    \n\u4f60\u662f\u8d22\u7ecf\u53e3\u64ad\u7a3f\u6539\u5199\u52a9\u624b\u3002\u6309\u4ee5\u4e0b\u89c4\u5219\u5904\u7406\u8f93\u5165：
    \n1. \u4fdd\u6301\u539f\u610f\u548c\u6570\u636e\u4e0d\u53d8，\u4e0d\u589e\u52a0\u9884\u6d4b，\u4e0d\u589e\u52a0\u8350\u80a1\u8868\u8ff0\u3002
    \n2. \u5355\u53e5\u5c3d\u91cf\u4e0d\u8d85\u8fc7 18-22 \u5b57，\u590d\u6742\u7ed3\u6784\u62c6\u6210\u4e24\u53e5\u3002
    \n3. \u628a\u672f\u8bed\u53e3\u8bed\u5316，\u4f8b\u5982：
    \n – "\u98ce\u9669\u504f\u597d\u6536\u655b" -> "\u5927\u5bb6\u66f4\u503e\u5411\u4e8e\u628a\u94b1\u63e1\u5728\u624b\u91cc，\u4e0d\u613f\u610f\u5192\u98ce\u9669"
    \n – "\u6d41\u52a8\u6027\u8fb9\u9645\u6536\u7d27" -> "\u5e02\u573a\u91cc\u7684\u94b1\u6ca1\u6709\u90a3\u4e48\u5bbd\u677e\u4e86"
    \n – "\u6280\u672f\u6027\u53cd\u5f39" -> "\u8dcc\u591a\u4e86\u5148\u6da8\u4e00\u6da8，\u4e0d\u7b49\u4e8e\u8d8b\u52bf\u53cd\u8f6c"
    \n4. \u6570\u5b57\u4fdd\u7559，\u4f46\u8865\u5145\u4e00\u53e5\u89e3\u91ca\u5176\u5f71\u54cd，\u4f8b\u5982：
    \n – "\u793e\u878d 8.7 \u4e07\u4ebf，\u540c\u6bd4\u591a\u589e" -> "\u793e\u878d\u662f 8.7 \u4e07\u4ebf，\u6bd4\u53bb\u5e74\u540c\u671f\u8981\u591a，\u8bf4\u660e\u501f\u94b1\u610f\u613f\u8d77\u6765\u4e86"
    \n5. \u7981\u6b62\u8f93\u51fa\u6295\u8d44\u5efa\u8bae\u3001\u76ee\u6807\u4ef7\u3001\u4e70\u5165\u5356\u51fa\u4fe1\u53f7\u3002
    \n"""<\/span><\/p>\n

    user_prompt =<\/span> f"""
    \n\u8bf7\u628a\u4e0b\u9762\u8fd9\u6bb5\u8d22\u7ecf\u6587\u7ae0\u6539\u5199\u6210\u53e3\u8bed\u5316\u53e3\u64ad\u7a3f，\u4fdd\u6301\u539f\u6570\u636e\u4e0d\u53d8：
    \n<\/span>{<\/span>article_text}<\/span><\/span>
    \n"""<\/span><\/span><\/p>\n

    \u8fd9\u91cc\u6709\u4e2a\u5173\u952e\u5751：LLM \u6539\u5199\u4f1a\u6539\u53d8\u539f\u610f，\u5c24\u5176\u662f\u6570\u5b57\u3001\u65e5\u671f\u3001\u767e\u5206\u6bd4\u3002\u8d22\u7ecf\u5185\u5bb9\u4e00\u6b21\u6539\u5199\u540e，\u5fc5\u987b\u628a\u539f\u7a3f\u548c\u53e3\u64ad\u7a3f\u5e76\u6392\u4eba\u5de5\u6838\u5bf9，\u786e\u8ba4\u6ca1\u6709\u201c8.7 \u4e07\u4ebf\u201d\u53d8\u201c8.8 \u4e07\u4ebf\u201d\u3001\u201c\u540c\u6bd4\u589e\u957f\u201d\u53d8\u201c\u73af\u6bd4\u589e\u957f\u201d\u8fd9\u7c7b\u786c\u4f24\u3002<\/p>\n

    \n

    \u4e00\u952e\u914d\u97f3\u600e\u4e48\u642d：edge-tts \u4e0e GPT-SoVITS \u4e24\u6761\u8def\u7ebf<\/h3>\n

    \u8def\u7ebf A：edge-tts \u5feb\u901f\u5408\u6210，\u9002\u5408\u6279\u91cf\u9a8c\u8bc1\u8282\u594f<\/h4>\n

    edge-tts \u662f\u5fae\u8f6f Edge \u6d4f\u89c8\u5668\u540c\u6e90 TTS \u7684\u5f00\u6e90\u5c01\u88c5，\u514d\u8d39\u3001\u65e0\u9700\u672c\u5730 GPU，\u9002\u5408\u5148\u628a\u53e3\u64ad\u7a3f\u8f6c\u6210\u97f3\u9891，\u7528\u6765\u68c0\u67e5\u65ad\u53e5\u548c\u65f6\u957f\u3002<\/p>\n

    pip install<\/span> edge-tts<\/p>\n

    \u751f\u6210\u914d\u97f3：<\/p>\n

    import<\/span> edge_tts
    \nimport<\/span> asyncio<\/p>\n

    text =<\/span> """
    \n\u4eca\u665a\u6709\u4e00\u6761\u6d88\u606f\u503c\u5f97\u804a\u4e00\u4e0b\u3002\u592e\u884c\u4eca\u5929\u516c\u5e03\u7684\u6700\u65b0\u793e\u878d\u6570\u636e，8.7 \u4e07\u4ebf，\u6bd4\u53bb\u5e74\u540c\u671f\u591a\u589e\u3002
    \n\u8fd9\u8bf4\u660e\u4ec0\u4e48？\u8bf4\u660e\u4f01\u4e1a\u548c\u5c45\u6c11\u501f\u94b1\u610f\u613f\u6bd4\u4e4b\u524d\u5f3a\u4e00\u70b9\u3002\u4f46\u8fd9\u4e2a\u6570\u636e\u4e0d\u80fd\u5355\u72ec\u770b，
    \n\u8fd8\u8981\u7ed3\u5408 M1 \u548c M2 \u4e00\u8d77\u5224\u65ad\u3002\u6211\u4eec\u6765\u8bf4\u4eba\u8bdd，M1 \u662f\u9a6c\u4e0a\u80fd\u82b1\u7684\u94b1，M2 \u662f\u968f\u65f6\u80fd\u52a8\u7684\u94b1\u3002
    \n"""<\/span><\/p>\n

    async<\/span> def<\/span> tts<\/span>(<\/span>)<\/span>:<\/span>
    \n tts_obj =<\/span> edge_tts.<\/span>Communicate(<\/span>
    \n text,<\/span>
    \n voice=<\/span>"zh-CN-XiaoxiaoNeural"<\/span>,<\/span>
    \n rate=<\/span>"+6%"<\/span>,<\/span>
    \n volume=<\/span>"+0%"<\/span>
    \n )<\/span>
    \n await<\/span> tts_obj.<\/span>save(<\/span>"output_uk_video.mp3"<\/span>)<\/span><\/p>\n

    asyncio.<\/span>run(<\/span>tts(<\/span>)<\/span>)<\/span><\/p>\n

    \u4f18\u70b9：\u96f6\u90e8\u7f72\u3001\u901f\u5ea6\u5feb，\u9002\u5408\u51fa demo\u3002
    \n\u7f3a\u70b9：\u97f3\u8272\u8f83\u5c11，\u957f\u65f6\u95f4\u53e3\u64ad\u7684\u8282\u594f\u504f\u7a33，\u4e0d\u591f\u201c\u50cf\u4eba\u201d\u3002<\/p>\n

    \u8def\u7ebf B：GPT-SoVITS \u514b\u9686\u56fa\u5b9a\u53e3\u64ad\u97f3\u8272<\/h4>\n

    \u5982\u679c\u4f60\u6709\u56fa\u5b9a\u680f\u76ee\u6216\u4e3b\u64ad\u4eba\u8bbe，\u9700\u8981\u6bcf\u671f\u58f0\u97f3\u4e00\u81f4，GPT-SoVITS \u66f4\u9002\u5408\u3002\u5b83\u7528\u5c11\u91cf\u5e72\u51c0\u4eba\u58f0\u8bad\u7ec3，\u8f93\u51fa\u7684\u662f\u540c\u4e00\u4e2a\u4eba\u58f0\u3002<\/p>\n

    git<\/span> clone https:\/\/github.com\/RVC-Boss\/GPT-SoVITS
    \ncd<\/span> GPT-SoVITS
    \npip install<\/span> -r<\/span> requirements.txt<\/p>\n

    \u8bad\u7ec3\u524d\u5fc5\u987b\u51c6\u5907\u65e0\u80cc\u666f\u97f3\u4e50\u3001\u65e0\u6df7\u54cd\u3001\u8bed\u901f\u7a33\u5b9a\u7684\u5355\u4eba\u58f0\u6837\u672c，\u65f6\u957f\u5efa\u8bae 5-20 \u5206\u949f\u3002\u8d22\u7ecf\u53f7\u5982\u679c\u8981\u7528 AI \u4e3b\u64ad，\u901a\u5e38\u8981\u5f55\u51e0\u6bb5\u7a33\u5b9a\u7684\u76d8\u9762\u590d\u76d8\u4eba\u58f0\u505a\u5e95\u6599\u3002<\/p>\n

    \u8bad\u7ec3\u7684\u5751\u5f88\u660e\u786e：\u53ea\u8981\u5e95\u6599\u91cc\u6709\u660e\u663e\u566a\u58f0\u6216\u7535\u6d41\u58f0，\u514b\u9686\u51fa\u6765\u7684\u97f3\u8272\u4f1a\u98d8，\u5c24\u5176\u5728\u201c\u6da8\u201d\u201c\u8dcc\u201d\u201c\u652f\u6491\u4f4d\u201d\u201c\u538b\u529b\u4f4d\u201d\u8fd9\u4e9b\u9ad8\u9891\u7387\u8bcd\u4e0a\u5bb9\u6613\u53d1\u865a\u3002\u56e0\u6b64，\u6210\u7247\u524d\u81f3\u5c11\u8981\u5b8c\u6574\u542c\u4e00\u904d\u5173\u952e\u6bb5\u843d\u3002<\/p>\n

    \n

    \u8d22\u7ecf\u5b57\u5e55\u600e\u4e48\u5bf9：faster-whisper \u751f\u6210\u65f6\u95f4\u8f74，\u518d\u5f3a\u5236\u5bf9\u9f50\u53e3\u64ad\u7a3f<\/h3>\n

    \u8d22\u7ecf\u4e13\u6709\u540d\u8bcd\u591a，\u76f4\u63a5\u8ba9\u8bed\u97f3\u8bc6\u522b\u6a21\u578b\u201c\u81ea\u7531\u53d1\u6325\u201d\u5bb9\u6613\u628a\u201cMACD\u201d\u8f6c\u6210\u201c\u9a6c\u514b D\u201d\u3001\u201c\u91d1\u53c9\u201d\u8f6c\u6210\u201c\u91d1\u64e6\u201d\u3002\u5de5\u7a0b\u4e0a\u66f4\u7a33\u7684\u505a\u6cd5\u662f：\u5148\u7528 faster-whisper \u505a\u521d\u8bc6\u522b，\u518d\u7528\u771f\u5b9e\u53e3\u64ad\u7a3f\u5f3a\u5236\u5bf9\u9f50\u3002<\/p>\n

    pip install<\/span> faster-whisper<\/p>\n

    from<\/span> faster_whisper import<\/span> WhisperModel<\/p>\n

    model =<\/span> WhisperModel(<\/span>"large-v3"<\/span>,<\/span> device=<\/span>"cpu"<\/span>,<\/span> compute_type=<\/span>"int8"<\/span>)<\/span><\/p>\n

    segments,<\/span> _ =<\/span> model.<\/span>transcribe(<\/span>
    \n "output_uk_video.mp3"<\/span>,<\/span>
    \n language=<\/span>"zh"<\/span>,<\/span>
    \n initial_prompt=<\/span>"\u8fd9\u662f\u4e00\u6bb5\u8d22\u7ecf\u53e3\u64ad，\u542b\u672f\u8bed：\u793e\u878d\u3001M1\u3001M2\u3001MACD\u3001\u91d1\u53c9\u3001\u6b7b\u53c9\u3001\u652f\u6491\u4f4d\u3001\u538b\u529b\u4f4d\u3002"<\/span>,<\/span>
    \n vad_filter=<\/span>True<\/span>
    \n)<\/span><\/p>\n

    with<\/span> open<\/span>(<\/span>"subtitle.srt"<\/span>,<\/span> "w"<\/span>,<\/span> encoding=<\/span>"utf-8"<\/span>)<\/span> as<\/span> f:<\/span>
    \n for<\/span> seg in<\/span> segments:<\/span>
    \n f.<\/span>write(<\/span>f"<\/span>{<\/span>seg.<\/span>start:<\/span>.3f<\/span>}<\/span><\/span> –> <\/span>{<\/span>seg.<\/span>end:<\/span>.3f<\/span>}<\/span><\/span>\\\\n<\/span>{<\/span>seg.<\/span>text}<\/span><\/span>\\\\n\\\\n"<\/span><\/span>)<\/span><\/p>\n

    \u7136\u540e\u628a\u8bc6\u522b\u51fa\u7684\u5b57\u5e55\u548c\u4f60\u7684\u53e3\u64ad\u7a3f\u505a\u4e00\u6b21 diff，\u91cd\u70b9\u68c0\u67e5\u6570\u5b57\u3001\u516c\u53f8\u540d\u3001\u6307\u6570\u540d\u3001\u5408\u7ea6\u540d，\u4e0d\u80fd\u76f4\u63a5\u91c7\u7528\u6a21\u578b\u7684\u88f8\u8f6c\u5199\u3002<\/p>\n

    \n

    \u8d22\u7ecf\u56fe\u8868\u548c\u8981\u70b9\u52a8\u753b：Manim \u753b K \u7ebf\u3001\u8d70\u52bf\u4e0e\u6570\u636e\u5361\u7247<\/h3>\n

    \u884c\u60c5\u5206\u6790\u6587\u6700\u5bb9\u6613\u201c\u5ff5\u6570\u5b57\u201d，\u753b\u9762\u5982\u679c\u4e0d\u8ddf\u4e0a，\u89c2\u4f17\u6839\u672c\u8bb0\u4e0d\u4f4f\u3002\u5f00\u6e90\u7684 Manim \u9002\u5408\u628a\u6587\u7ae0\u91cc\u7684\u5173\u952e\u56fe\u8868\u7a0b\u5e8f\u5316\u751f\u6210，\u4fdd\u8bc1\u6bcf\u4e00\u4e2a\u70b9\u4f4d\u3001\u6bcf\u4e00\u6839 K \u7ebf\u4e0e\u771f\u5b9e\u884c\u60c5\u4e00\u81f4\u3002<\/p>\n

    pip install<\/span> manim<\/p>\n

    \u4e0b\u9762\u8fd9\u6bb5\u53ef\u76f4\u63a5\u6e32\u67d3\u4e00\u6bb5\u201c\u4e0a\u6da8\u540e\u56de\u8e29\u538b\u529b\u4f4d\u201d\u7684\u793a\u610f\u52a8\u753b：<\/p>\n

    from<\/span> manim import<\/span> *<\/span><\/p>\n

    class<\/span> PriceBreak<\/span>(<\/span>Scene)<\/span>:<\/span>
    \n def<\/span> construct<\/span>(<\/span>self)<\/span>:<\/span>
    \n axes =<\/span> Axes(<\/span>
    \n x_range=<\/span>[<\/span>0<\/span>,<\/span> 10<\/span>,<\/span> 1<\/span>]<\/span>,<\/span>
    \n y_range=<\/span>[<\/span>0<\/span>,<\/span> 10<\/span>,<\/span> 1<\/span>]<\/span>,<\/span>
    \n axis_config=<\/span>{<\/span>"include_numbers"<\/span>:<\/span> True<\/span>}<\/span>,<\/span>
    \n )<\/span>
    \n price_line =<\/span> VMobject(<\/span>)<\/span>
    \n points =<\/span> [<\/span>
    \n axes.<\/span>c2p(<\/span>0<\/span>,<\/span> 2<\/span>)<\/span>,<\/span>
    \n axes.<\/span>c2p(<\/span>2<\/span>,<\/span> 3.5<\/span>)<\/span>,<\/span>
    \n axes.<\/span>c2p(<\/span>3<\/span>,<\/span> 3.0<\/span>)<\/span>,<\/span>
    \n axes.<\/span>c2p(<\/span>4<\/span>,<\/span> 4.2<\/span>)<\/span>,<\/span>
    \n axes.<\/span>c2p(<\/span>5<\/span>,<\/span> 3.7<\/span>)<\/span>,<\/span>
    \n axes.<\/span>c2p(<\/span>6<\/span>,<\/span> 4.8<\/span>)<\/span>,<\/span>
    \n axes.<\/span>c2p(<\/span>8<\/span>,<\/span> 6.0<\/span>)<\/span>,<\/span>
    \n ]<\/span>
    \n price_line.<\/span>set_points_as_corners(<\/span>points)<\/span>
    \n pressure_line =<\/span> DashedLine(<\/span>
    \n axes.<\/span>c2p(<\/span>0<\/span>,<\/span> 6.0<\/span>)<\/span>,<\/span>
    \n axes.<\/span>c2p(<\/span>9<\/span>,<\/span> 6.0<\/span>)<\/span>,<\/span>
    \n color=<\/span>RED
    \n )<\/span>
    \n label =<\/span> Text(<\/span>"\u538b\u529b\u4f4d 6.0"<\/span>,<\/span> font=<\/span>"Noto Sans CJK SC"<\/span>)<\/span>.<\/span>next_to(<\/span>pressure_line,<\/span> UP)<\/span><\/p>\n

    self.<\/span>play(<\/span>Create(<\/span>axes)<\/span>,<\/span> run_time=<\/span>1.5<\/span>)<\/span>
    \n self.<\/span>play(<\/span>Create(<\/span>price_line)<\/span>,<\/span> run_time=<\/span>3<\/span>)<\/span>
    \n self.<\/span>play(<\/span>Create(<\/span>pressure_line)<\/span>,<\/span> Write(<\/span>label)<\/span>,<\/span> run_time=<\/span>2<\/span>)<\/span><\/p>\n

    \u6e32\u67d3\u547d\u4ee4：<\/p>\n

    manim -pql<\/span> price_break.py PriceBreak<\/p>\n

    Manim \u66f4\u9002\u5408\u505a\u201c\u5173\u952e\u70b9\u4f4d\u6f14\u793a\u201d\u201c\u8d44\u91d1\u6d41\u5411\u62c6\u89e3\u201d\u201c\u653f\u7b56\u4f20\u5bfc\u94fe\u6761\u201d\u8fd9\u7c7b\u62bd\u8c61\u89e3\u91ca，\u800c\u4e0d\u662f\u76f4\u63a5\u628a\u6574\u7bc7\u884c\u60c5\u6587\u7ae0\u505a\u6210\u8fde\u7eed\u52a8\u753b\u3002\u5b83\u7684\u5b66\u4e60\u6210\u672c\u504f\u9ad8，\u5efa\u8bae\u53ea\u628a\u6587\u4e2d\u4e24\u4e09\u4e2a\u4e0d\u753b\u56fe\u5c31\u8bb2\u4e0d\u6e05\u7684\u70b9\u505a\u6210\u52a8\u753b，\u5176\u4f59\u753b\u9762\u7528\u5b57\u5e55\u548c\u5b9e\u62cd\u7d20\u6750\u5b8c\u6210\u3002<\/p>\n

    \n

    \u6700\u540e\u4e00\u6b65：FFmpeg \u5408\u6210\u914d\u97f3\u3001\u5b57\u5e55\u3001\u56fe\u8868\u548c\u6210\u7247<\/h3>\n

    \u5230\u8fd9\u4e00\u6b65，\u624b\u91cc\u4f1a\u6709：<\/p>\n

      \n
    • \u914d\u97f3\u97f3\u9891：voice.mp3<\/li>\n
    • \u5b57\u5e55：subtitle.srt<\/li>\n
    • Manim \u6e32\u67d3\u51fa\u7684\u56fe\u8868\u89c6\u9891：chart.mp4<\/li>\n
    • \u80cc\u666f\u7d20\u6750\u6216\u5f55\u5c4f：bg.mp4<\/li>\n
    • \u539f\u53e3\u64ad\u7a3f：script.txt<\/li>\n<\/ul>\n

      \u7528 FFmpeg \u7edf\u4e00\u5408\u6210：<\/p>\n

      # \u5148\u628a\u5b57\u5e55\u70e7\u5f55\u5230\u80cc\u666f\u753b\u9762\u4e0a，\u5e76\u628a\u914d\u97f3\u548c\u80cc\u666f\u5408\u6210<\/span>
      \nffmpeg -y<\/span> \\\\<\/span>
      \n -i<\/span> bg.mp4 \\\\<\/span>
      \n -i<\/span> voice.mp3 \\\\<\/span>
      \n -vf<\/span> "subtitles=subtitle.srt:force_style='FontName=Noto Sans CJK SC,FontSize=20,PrimaryColour=&H00FFFFFF&'"<\/span> \\\\<\/span>
      \n -c:v<\/span> libx264 -preset<\/span> medium -crf<\/span> 20<\/span> \\\\<\/span>
      \n -c:a<\/span> aac -b:a<\/span> 192k \\\\<\/span>
      \n -shortest<\/span> \\\\<\/span>
      \n output.mp4<\/p>\n

      \u5b57\u5e55\u4f4d\u7f6e\u3001\u5b57\u4f53\u5927\u5c0f\u9700\u8981\u6839\u636e\u7ad6\u5c4f\u8fd8\u662f\u6a2a\u5c4f\u624b\u52a8\u8c03\u6574\u3002FFmpeg \u7684 subtitles \u6ee4\u955c\u4f9d\u8d56 libass，\u4e2d\u6587\u5b57\u4f53\u8def\u5f84\u5728\u4e0d\u540c\u7cfb\u7edf\u4e0a\u7ecf\u5e38\u4e0d\u4e00\u81f4，\u5efa\u8bae\u5728\u9879\u76ee\u91cc\u663e\u5f0f\u6307\u5b9a\u5b57\u4f53\u76ee\u5f55\u3002<\/p>\n

      \n

      \u5168\u624b\u52a8\u5230\u534a\u81ea\u52a8：\u5f00\u6e90\u5de5\u5177\u94fe vs \u5546\u4e1a\u6253\u5305\u65b9\u6848\u600e\u4e48\u9009<\/h3>\n

      \u5168\u624b\u52a8\u5f00\u6e90\u81ea\u5efa\u5de5\u4f5c\u6d41<\/h4>\n\n\u73af\u8282\u5f00\u6e90\u5de5\u5177\u5355\u6b21\u8017\u65f6\u4e3b\u8981\u6210\u672c<\/tr>\n\n\n\n\n\n\n\n
      \u53e3\u64ad\u7a3f\u6539\u5199<\/td>\nLLM + \u4eba\u5de5\u6838\u7a3f<\/td>\n15-30 \u5206\u949f<\/td>\n\u6570\u5b57\u539f\u610f\u6838\u5bf9<\/td>\n<\/tr>\n
      \u914d\u97f3<\/td>\nedge-tts \/ GPT-SoVITS<\/td>\n5-20 \u5206\u949f<\/td>\n\u97f3\u8272\u8bad\u7ec3\u3001\u8bd5\u542c<\/td>\n<\/tr>\n
      \u5b57\u5e55<\/td>\nfaster-whisper + \u5bf9\u9f50<\/td>\n10-20 \u5206\u949f<\/td>\n\u8d22\u7ecf\u672f\u8bed\u6821\u6b63<\/td>\n<\/tr>\n
      \u56fe\u8868\u52a8\u753b<\/td>\nManim<\/td>\n2-6 \u5c0f\u65f6<\/td>\n\u5b66\u4e60\u66f2\u7ebf<\/td>\n<\/tr>\n
      \u5408\u6210\u6210\u7247<\/td>\nFFmpeg<\/td>\n10-20 \u5206\u949f<\/td>\n\u53c2\u6570\u8c03\u8bd5<\/td>\n<\/tr>\n
      \u6574\u4f53<\/td>\n\u2014<\/td>\n2.5-7 \u5c0f\u65f6<\/td>\n\u73af\u5883\u7ef4\u62a4<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      \u8fd9\u5957\u65b9\u6848\u7684\u4f18\u52bf\u662f\u53ef\u63a7，\u52a3\u52bf\u662f\u73af\u5883\u642d\u5efa\u548c Manim \u5b66\u4e60\u6210\u672c\u9ad8\u3002\u9002\u5408\u201c\u60f3\u628a\u5b83\u505a\u6210\u56fa\u5b9a\u6280\u672f\u6808\u201d\u7684\u56e2\u961f\u3002<\/p>\n

      \u534a\u81ea\u52a8\u7ebf\u8def：\u628a\u4e2d\u95f4\u5c42\u6253\u5305\u6389<\/h4>\n

      \u5982\u679c\u4e0d\u60f3\u7ef4\u62a4\u6574\u5957\u5f00\u6e90\u5de5\u5177，\u53ef\u4ee5\u7528\u82b1\u751fAI \u4f5c\u4e3a\u4e2d\u95f4\u5c42，\u628a\u201c\u53e3\u64ad\u7a3f\u6539\u5199 + \u914d\u97f3 + \u5b57\u5e55 + \u753b\u9762\u5339\u914d\u201d\u6253\u5305\u5904\u7406\u3002\u5b9e\u9645\u4f7f\u7528\u5f62\u6001\u662f：\u8f93\u5165\u6574\u7406\u597d\u7684\u8d22\u7ecf\u53e3\u64ad\u7a3f，\u76f4\u63a5\u751f\u6210\u5e26\u914d\u97f3\u3001\u5b57\u5e55\u548c\u7d20\u6750\u753b\u9762\u7684\u6210\u7247\u3002\u5bf9\u8d22\u7ecf\u53f7\u4f5c\u8005\u7684\u6536\u76ca\u662f，\u4fe1\u606f\u5bc6\u5ea6\u9ad8\u3001\u5f53\u5929\u706b\u70ed\u70b9\u9700\u8981\u5feb\u901f\u51fa\u7247\u65f6，\u53ef\u4ee5\u628a\u201c\u4ece\u6587\u7ae0\u5230\u6210\u7247\u201d\u538b\u7f29\u5230\u66f4\u77ed\u65f6\u95f4\u3002<\/p>\n

      \u4f46\u4e0d\u80fd\u628a\u5b83\u7406\u89e3\u6210\u201c\u81ea\u52a8\u5408\u89c4\u5668\u201d\u3002\u9700\u8981\u660e\u786e\u8bf4\u4e00\u53e5：\u82b1\u751fAI \u4e0d\u505a\u8d22\u7ecf\u5185\u5bb9\u7684\u5408\u89c4\u5ba1\u6838，\u4e0d\u5224\u65ad\u6587\u5b57\u91cc\u6709\u6ca1\u6709\u8350\u80a1\u3001\u6536\u76ca\u627f\u8bfa\u6216\u8bef\u5bfc\u6027\u8868\u8ff0，\u8fd9\u7c7b\u5224\u65ad\u53ea\u80fd\u7531\u4f5c\u8005\u81ea\u5df1\u5b8c\u6210\u3002 \u53e3\u64ad\u7a3f\u53e3\u8bed\u5316\u7a0b\u5ea6\u662f\u5426\u7b26\u5408\u4f60\u7684\u8d26\u53f7\u98ce\u683c，\u914d\u97f3\u97f3\u8272\u662f\u5426\u9700\u8981\u6362，\u5173\u952e\u6570\u5b57\u662f\u5426\u6709\u8bef，\u4ecd\u9700\u4eba\u5de5\u7ec8\u5ba1\u3002<\/p>\n

      \u591a\u5de5\u5177\u5206\u5de5\u5bf9\u6bd4<\/h4>\n\n\u5de5\u5177\u5b9a\u4f4d\u9002\u5408\u8c01<\/tr>\n\n\n\n\n\n\n\n\n
      edge-tts<\/td>\n\u5feb\u901f TTS，\u5355\u6761\u9a8c\u8bc1<\/td>\n\u4e0d\u6311\u97f3\u8272\u3001\u8ffd\u65f6\u6548\u7684\u4f5c\u8005<\/td>\n<\/tr>\n
      GPT-SoVITS<\/td>\n\u514b\u9686\u56fa\u5b9a\u97f3\u8272<\/td>\n\u6709\u56fa\u5b9a\u4e3b\u64ad\u4eba\u8bbe\u3001\u957f\u671f\u680f\u76ee<\/td>\n<\/tr>\n
      faster-whisper<\/td>\n\u8d22\u7ecf\u5b57\u5e55\u521d\u8f6c + \u5bf9\u9f50<\/td>\n\u6240\u6709\u9700\u4e0a\u5b57\u5e55\u7684\u53e3\u64ad\u89c6\u9891<\/td>\n<\/tr>\n
      Manim<\/td>\n\u56fe\u8868\/\u70b9\u4f4d\/\u903b\u8f91\u52a8\u753b<\/td>\n\u884c\u60c5\u5206\u6790\u3001\u77e5\u8bc6\u62c6\u89e3\u89c6\u9891<\/td>\n<\/tr>\n
      FFmpeg<\/td>\n\u5408\u6210\u3001\u70e7\u5b57\u5e55\u3001\u538b\u5236<\/td>\n\u6240\u6709\u6210\u7247\u51fa\u53e3<\/td>\n<\/tr>\n
      \u526a\u6620 \/ \u5fc5\u526a<\/td>\n\u624b\u52a8\u526a\u8f91\u8865\u5145<\/td>\nAI \u7c97\u526a\u540e\u7cbe\u4fee\u3001\u52a0\u8d34\u7eb8\u3001\u505a\u5c01\u9762<\/td>\n<\/tr>\n
      \u82b1\u751fAI<\/td>\n\u6587\u7a3f\/\u53e3\u64ad\u5230\u6210\u7247\u534a\u81ea\u52a8\u6253\u5305<\/td>\n\u4e0d\u60f3\u7ef4\u62a4\u5f00\u6e90\u73af\u5883\u3001\u6279\u91cf\u51fa\u7247<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      \u5bf9\u666e\u901a\u8d22\u7ecf\u81ea\u5a92\u4f53\u6765\u8bf4，\u6bd4\u8f83\u52a1\u5b9e\u7684\u8def\u5f84\u4e0d\u662f\u4e8c\u9009\u4e00，\u800c\u662f\u6df7\u5408：\u70ed\u70b9\u8d44\u8baf\u7a3f\u8d70\u534a\u81ea\u52a8\u6210\u7247，\u6df1\u5ea6\u884c\u60c5\u6587\u7528\u5f00\u6e90\u5de5\u5177\u7cbe\u4fee\u3002\u524d\u8005\u6293\u65f6\u6548，\u540e\u8005\u6293\u4fe1\u4efb\u611f\u3002<\/p>\n

      \n

      \u4e09\u6761\u6700\u5bb9\u6613\u7ffb\u8f66\u7684\u5de5\u7a0b\u7ec6\u8282<\/h3>\n
    • \n

      \u53e3\u64ad\u7a3f\u6539\u5199\u4f1a\u628a\u201c\u540c\u6bd4\u201d\u6539\u6210\u201c\u73af\u6bd4\u201d
      \nLLM \u91cd\u5199\u65f6\u5bf9\u7edf\u8ba1\u53e3\u5f84\u4e0d\u654f\u611f，\u5fc5\u987b\u4eba\u5de5\u56de\u770b\u3002\u201c\u540c\u6bd4\u591a\u589e\u201d\u548c\u201c\u73af\u6bd4\u591a\u589e\u201d\u5728\u8d22\u7ecf\u5185\u5bb9\u91cc\u662f\u5b8c\u5168\u4e0d\u540c\u7ed3\u8bba\u3002<\/p>\n<\/li>\n

    • \n

      whisper \u4e13\u6709\u540d\u8bcd\u8f6c\u5199\u4e0d\u51c6
      \n\u5149\u9760 initial_prompt \u6ce8\u5165\u672f\u8bed\u8fd8\u4e0d\u591f，\u6700\u540e\u5b57\u5e55\u5fc5\u987b\u4e0e\u53e3\u64ad\u7a3f\u505a\u5bf9\u9f50\u6821\u6b63，\u5426\u5219\u201cM1\u201d\u53d8\u201c\u534f\u8bae\u201d\u3001\u201cKDJ\u201d\u53d8\u201c\u51ef\u8fea\u91d1\u201d，\u53d1\u51fa\u53bb\u5c31\u662f\u4e8b\u6545\u3002<\/p>\n<\/li>\n

    • \n

      \u56fe\u8868\u6570\u636e\u4e0d\u80fd\u7528\u751f\u6210\u5f0f AI \u76f4\u63a5\u9020
      \n\u884c\u60c5\u56fe\u3001\u70b9\u4f4d\u56fe\u5fc5\u987b\u4ece\u771f\u5b9e\u6570\u636e\u6e90\u7a0b\u5e8f\u5316\u751f\u6210，\u4e0d\u80fd\u8ba9\u751f\u6210\u6a21\u578b\u81ea\u5df1\u753b\u3002\u5c24\u5176\u505a\u201c\u6307\u6570\u8d70\u52bf\u201d\u201c\u677f\u5757\u6da8\u8dcc\u5e45\u6392\u884c\u201d\u65f6，\u5148\u8fc7 Wind\u3001\u540c\u82b1\u987a\u3001\u4ea4\u6613\u6240\u5b98\u7f51\u7b49\u6570\u636e\u6e90，\u518d\u624b\u52a8\u5199\u6210\u56fe\u8868\u811a\u672c\u3002<\/p>\n<\/li>\n

      \n

      \u5408\u89c4\u5fc5\u987b\u5148\u4e8e\u5de5\u5177<\/h3>\n

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