{"id":4768,"date":"2026-01-16T17:57:37","date_gmt":"2026-01-16T09:57:37","guid":{"rendered":"https:\/\/www.15zhi.net\/blog\/?p=4768"},"modified":"2026-01-16T17:57:37","modified_gmt":"2026-01-16T09:57:37","slug":"202601-%e8%ae%ba%e6%96%87%e7%a0%94%e8%af%bb-immersediffusion-a-generative-spatial-audio-latent-diffusion-model","status":"publish","type":"post","link":"https:\/\/www.15zhi.net\/blog\/202601-%e8%ae%ba%e6%96%87%e7%a0%94%e8%af%bb-immersediffusion-a-generative-spatial-audio-latent-diffusion-model\/","title":{"rendered":"202601 \u8bba\u6587\u7814\u8bfb-ImmerseDiffusion: A Generative Spatial Audio Latent Diffusion Model"},"content":{"rendered":"\n

\u4f5c\u8005\uff1aMojtaba Heydari\uff0cMehrez Souden\uff0cBruno Conejo\uff0cJoshua Atkins<\/p>\n\n\n\n

\u4f5c\u8005\u5355\u4f4d\uff1aUniversity of Rochester\uff08\u7f57\u5207\u65af\u7279\u5927\u5b66\uff09\uff0cApple\uff08\u82f9\u679c\u516c\u53f8\uff09<\/p>\n\n\n\n

\u6765\u6e90\uff1aarXiv<\/p>\n\n\n\n

\u65f6\u95f4\uff1a2025\u5e742\u67087\u65e5<\/p>\n\n\n\n

\u80cc\u666f<\/h2>\n\n\n\n

\u968f\u7740\u865a\u62df\u73b0\u5b9e\u3001\u589e\u5f3a\u73b0\u5b9e\u3001\u6e38\u620f\u3001\u5f71\u89c6\u5236\u4f5c\u4ee5\u53ca\u6c89\u6d78\u5f0f\u4ea4\u4e92\u7cfb\u7edf\u7684\u53d1\u5c55\uff0c\u5bf9\u9ad8\u771f\u5b9e\u611f\u4e09\u7ef4\u7a7a\u95f4\u97f3\u9891\uff083D Spatial Audio\uff09\u7684\u9700\u6c42\u4e0d\u65ad\u589e\u957f\u3002\u76f8\u6bd4\u4f20\u7edf\u7684\u5355\u58f0\u9053\u6216\u7acb\u4f53\u58f0\u97f3\u9891\uff0c\u7a7a\u95f4\u97f3\u9891\u80fd\u591f\u5728\u65b9\u4f4d\u3001\u9ad8\u5ea6\u548c\u8ddd\u79bb\u7b49\u7ef4\u5ea6\u4e0a\u51c6\u786e\u5448\u73b0\u58f0\u6e90\u4f4d\u7f6e\uff0c\u4ece\u800c\u663e\u8457\u589e\u5f3a\u6c89\u6d78\u4f53\u9a8c \u3002\u8fd1\u5e74\u6765\uff0c\u57fa\u4e8e\u6269\u6563\u6a21\u578b\uff08Diffusion Models\uff09\u7684\u751f\u6210\u5f0f\u97f3\u9891\u65b9\u6cd5\u53d6\u5f97\u4e86\u663e\u8457\u8fdb\u5c55\uff0c\u5982 AudioLDM\u3001Stable Audio \u7b49\u6a21\u578b\u5df2\u80fd\u591f\u6839\u636e\u6587\u672c\u751f\u6210\u9ad8\u8d28\u91cf\u97f3\u9891\u5185\u5bb9\u3002\u7136\u800c\uff0c\u8fd9\u4e9b\u65b9\u6cd5\u5927\u591a\u5c40\u9650\u4e8e\u5355\u58f0\u9053\u6216\u7acb\u4f53\u58f0\uff0c\u7f3a\u4e4f\u5bf9\u58f0\u6e90\u7a7a\u95f4\u4f4d\u7f6e\u7684\u7cbe\u786e\u5efa\u6a21\u80fd\u529b\uff0c\u96be\u4ee5\u6839\u636e\u7528\u6237\u6307\u4ee4\u5c06\u58f0\u97f3\u51c6\u786e\u653e\u7f6e\u5728\u6307\u5b9a\u65b9\u5411\u6216\u7a7a\u95f4\u4f4d\u7f6e\u3002<\/p>\n\n\n\n

\u4e3b\u8981\u8d21\u732e<\/h2>\n\n\n\n

\u672c\u6587\u63d0\u51fa\u4e86 ImmerseDiffusion<\/strong>\uff0c\u4e00\u79cd\u7aef\u5230\u7aef\u7684\u751f\u6210\u5f0f\u7a7a\u95f4\u97f3\u9891\u6269\u6563\u6a21\u578b\uff0c\u5176\u4e3b\u8981\u8d21\u732e\u5305\u62ec\uff1a<\/p>\n\n\n\n

    \n
  1. \u9996\u6b21\u63d0\u51fa\u9762\u5411\u4e09\u7ef4\u7a7a\u95f4\u97f3\u9891\u7684\u751f\u6210\u5f0f\u6269\u6563\u6a21\u578b<\/strong>
    \u4f5c\u8005\u63d0\u51fa\u4e86\u9996\u4e2a\u80fd\u591f\u76f4\u63a5\u751f\u6210\u4e00\u9636 Ambisonics\uff08FOA\uff09\u683c\u5f0f\u7a7a\u95f4\u97f3\u9891\u7684\u751f\u6210\u6a21\u578b\uff0c\u5b9e\u73b0\u5bf9\u65b9\u4f4d\u89d2\u3001\u9ad8\u5ea6\u548c\u8ddd\u79bb\u7b49\u7a7a\u95f4\u5c5e\u6027\u7684\u5efa\u6a21 \u3002<\/li>\n\n\n\n
  2. \u8bbe\u8ba1\u4e86\u53cc\u6a21\u5f0f\u7a7a\u95f4\u63a7\u5236\u673a\u5236<\/strong>
    \u6a21\u578b\u652f\u6301\u4e24\u79cd\u751f\u6210\u65b9\u5f0f\uff1a\n
      \n
    • \u63cf\u8ff0\u5f0f\uff08Descriptive\uff09\u6a21\u5f0f<\/strong>\uff1a\u901a\u8fc7\u5305\u542b\u7a7a\u95f4\u4e0e\u73af\u5883\u4fe1\u606f\u7684\u81ea\u7136\u8bed\u8a00\u6587\u672c\u63a7\u5236\u97f3\u9891\u751f\u6210\uff1b<\/li>\n\n\n\n
    • \u53c2\u6570\u5f0f\uff08Parametric\uff09\u6a21\u5f0f<\/strong>\uff1a\u7ed3\u5408\u975e\u7a7a\u95f4\u6587\u672c\u63cf\u8ff0\u4e0e\u663e\u5f0f\u6570\u503c\u5316\u7a7a\u95f4\u53c2\u6570\uff0c\u5b9e\u73b0\u7cbe\u786e\u3001\u53ef\u63a7\u7684\u7a7a\u95f4\u97f3\u9891\u751f\u6210\uff0c\u9002\u7528\u4e8e\u6e38\u620f\u5f15\u64ce\u548c\u4eff\u771f\u7cfb\u7edf\u7b49\u573a\u666f \u3002<\/li>\n<\/ul>\n<\/li>\n\n\n\n
    • \u63d0\u51fa\u9488\u5bf9\u7a7a\u95f4\u97f3\u9891\u751f\u6210\u7684\u7cfb\u7edf\u5316\u8bc4\u4f30\u6307\u6807<\/strong>
      \u9488\u5bf9 FOA \u7a7a\u95f4\u97f3\u9891\u751f\u6210\uff0c\u4f5c\u8005\u5f15\u5165\u5e76\u6539\u8fdb\u4e86\u5305\u62ec Ambisonics FAD\u3001\u7a7a\u95f4 KL \u6563\u5ea6\u3001\u7a7a\u95f4 CLAP \u5f97\u5206\u4ee5\u53ca\u57fa\u4e8e\u58f0\u5f3a\u5411\u91cf\u7684\u7a7a\u95f4\u5b9a\u4f4d\u8bef\u5dee\u6307\u6807\uff0c\u7528\u4e8e\u5168\u9762\u8bc4\u4f30\u751f\u6210\u97f3\u9891\u7684\u8d28\u91cf\u4e0e\u7a7a\u95f4\u4e00\u81f4\u6027 \u3002<\/li>\n<\/ol>\n\n\n\n

      \u6280\u672f\u65b9\u6cd5<\/h2>\n\n\n\n
      \"\"<\/figure>\n\n\n\n

      \u672c\u6587\u63d0\u51fa\u7684 ImmerseDiffusion \u662f\u4e00\u4e2a\u7aef\u5230\u7aef\u7684\u751f\u6210\u5f0f\u7a7a\u95f4\u97f3\u9891\u7cfb\u7edf\uff0c\u76ee\u6807\u662f\u5728\u7528\u6237\u6761\u4ef6\u7ea6\u675f\u4e0b\u751f\u6210 \u4e00\u9636 Ambisonics\uff08FOA\uff09\u56db\u901a\u9053\u7a7a\u95f4\u97f3\u9891\u3002\u6574\u4f53\u65b9\u6cd5\u7531\u4e09\u90e8\u5206\u7ec4\u6210\uff1aFOA \u7a7a\u95f4\u97f3\u9891\u7f16\u7801\u5668\uff08Codec\uff09\u3001\u6761\u4ef6\u63a7\u5236\u6a21\u5757\uff08Conditioner\uff09\u4ee5\u53ca\u57fa\u4e8e Transformer \u7684\u6f5c\u7a7a\u95f4\u6269\u6563\u6a21\u578b\uff08Diffusion Transformer\uff09\u3002<\/p>\n\n\n\n

      1\uff09\u7a7a\u95f4\u97f3\u9891\u8868\u793a\uff1aFOA\uff08First-Order Ambisonics\uff09<\/h5>\n\n\n\n

      \u7cfb\u7edf\u751f\u6210\u7684\u7a7a\u95f4\u97f3\u9891\u91c7\u7528 FOA \u683c\u5f0f\uff0c\u5305\u542b W\u3001X\u3001Y\u3001Z \u56db\u4e2a\u901a\u9053\uff1aW \u4e3a\u5168\u5411\u5206\u91cf\uff0cX\/Y\/Z \u4e3a\u65b9\u5411\u5206\u91cf\uff0c\u5206\u522b\u8868\u8fbe\u524d\u540e\u3001\u5de6\u53f3\u3001\u4e0a\u4e0b\u65b9\u5411\u4fe1\u606f\u3002\u8be5\u8868\u793a\u80fd\u591f\u901a\u8fc7\u6e32\u67d3\u8f6c\u6362\u5230\u591a\u58f0\u9053\u7a7a\u95f4\u8f93\u51fa\uff0c\u662f\u5e38\u7528\u7684\u6c89\u6d78\u5f0f\u97f3\u9891\u683c\u5f0f\u3002<\/p>\n\n\n\n

      2\uff09\u7a7a\u95f4\u97f3\u9891\u7f16\u7801\u5668\uff1aFOA Codec \u5c06\u6ce2\u5f62\u538b\u7f29\u5230\u6f5c\u7a7a\u95f4<\/p>\n\n\n\n

      \u7531\u4e8e FOA \u97f3\u9891\u6570\u636e\u7ef4\u5ea6\u9ad8\u3001\u6269\u6563\u8fed\u4ee3\u8ba1\u7b97\u91cf\u5927\uff0c\u4f5c\u8005\u5148\u8bad\u7ec3\u4e00\u4e2a \u7a7a\u95f4\u97f3\u9891\u81ea\u7f16\u7801\u5668\uff08Ambisonic autoencoder \/ codec\uff09<\/strong>\uff0c\u5c06 FOA \u6ce2\u5f62\u6620\u5c04\u5230\u4f4e\u7ef4\u8fde\u7eed\u6f5c\u7a7a\u95f4\uff0c\u518d\u5728\u6f5c\u7a7a\u95f4\u8fdb\u884c\u6269\u6563\u751f\u6210\uff0c\u4ee5\u63d0\u5347\u6548\u7387\u3002<\/p>\n\n\n\n

      3\uff09\u6761\u4ef6\u63a7\u5236\u6a21\u5757\uff1a\u63cf\u8ff0\u5f0f\u4e0e\u53c2\u6570\u5f0f\u4e24\u79cd\u6a21\u5f0f<\/p>\n\n\n\n

      \u4e3a\u5b9e\u73b0\u7528\u6237\u53ef\u63a7\u7684\u7a7a\u95f4\u97f3\u9891\u751f\u6210\uff0c\u6a21\u578b\u8bbe\u8ba1\u4e86\u4e24\u5957\u6761\u4ef6\u8f93\u5165\u65b9\u5f0f\uff0c\u5e76\u5728\u6269\u6563\u7f51\u7edc\u4e2d\u901a\u8fc7 cross-attention \u7b49\u673a\u5236\u6ce8\u5165\u6761\u4ef6\u4fe1\u606f\u3002\u5728\u63cf\u8ff0\u5f0f\u6a21\u578b<\/strong>\u4e2d\uff0c\u4f7f\u7528 ELSA \u7a7a\u95f4\u6587\u672c\u7f16\u7801\u5668\u63d0\u53d6\u5305\u542b\u7a7a\u95f4\u4e0e\u73af\u5883\u8bed\u4e49\u7684\u6587\u672c\u5d4c\u5165\uff1b\u5728\u53c2\u6570\u5f0f\u6a21\u578b<\/strong>\u4e2d\uff0c\u91c7\u7528 LAION CLAP \u6587\u672c\u7f16\u7801\u5668\u5904\u7406\u975e\u7a7a\u95f4\u6587\u672c\uff0c\u5e76\u5f15\u5165\u663e\u5f0f\u6570\u503c\u53c2\u6570\uff08\u65b9\u4f4d\u89d2\u3001\u9ad8\u5ea6\u3001\u8ddd\u79bb\u3001\u623f\u95f4\u5927\u5c0f\u3001\u6df7\u54cd\u65f6\u95f4\u7b49\uff09\u4f5c\u4e3a\u6761\u4ef6\u8f93\u5165\uff1b\u540c\u65f6\uff0c\u4e24\u79cd\u6a21\u578b\u5747\u5f15\u5165\u65f6\u95f4\u6761\u4ef6\uff08\u8d77\u59cb\u65f6\u95f4\u4e0e\u603b\u65f6\u957f\uff09\u4ee5\u5b9e\u73b0\u65f6\u95f4\u53ef\u63a7\u751f\u6210\u3002<\/p>\n\n\n\n

      4\uff09\u6f5c\u7a7a\u95f4\u6269\u6563\u6a21\u578b\uff1aDiffusion Transformer \u8fdb\u884c\u6761\u4ef6\u53bb\u566a\u751f\u6210<\/p>\n\n\n\n

      \u5728\u6f5c\u5728\u7a7a\u95f4\u4e2d\uff0c\u4f5c\u8005\u91c7\u7528 Diffusion Transformer\uff08DiT\uff09\u7ed3\u6784\u4f5c\u4e3a\u6269\u6563\u7f51\u7edc\uff0c\u7ed3\u5408\u81ea\u6ce8\u610f\u529b\u3001\u4ea4\u53c9\u6ce8\u610f\u529b\u4e0e\u95e8\u63a7 MLP \u6a21\u5757\uff0c\u5b9e\u73b0\u591a\u6a21\u6001\u6761\u4ef6\u5bf9\u97f3\u9891\u751f\u6210\u8fc7\u7a0b\u7684\u6709\u6548\u5f15\u5bfc\u3002<\/p>\n\n\n\n

      \u5b9e\u9a8c\u5206\u6790<\/h2>\n\n\n\n

      \u6570\u636e\u96c6<\/strong>\uff1a\u4f5c\u8005\u4f7f\u7528\u4e86\u591a\u5957\u201c\u5408\u6210\u7a7a\u95f4\u5316\u201d\u7684\u6570\u636e\u6765\u8bad\u7ec3 FOA codec \u4e0e\u4e24\u79cd ImmerseDiffusion \u6a21\u578b\uff0c\u5305\u62ec Spatial FreeSound\u3001Spatial AudioCaps\u3001Spatial Clotho\uff0c\u5e76\u989d\u5916\u52a0\u5165 Spatial LibriSpeech \u4e0e\u5bf9\u5e94\u7684 FOA \u566a\u58f0\u6570\u636e\u4ee5\u63d0\u5347\u8bed\u97f3\u6cdb\u5316\u80fd\u529b\uff1b\u6bcf\u6761\u6570\u636e\u90fd\u5305\u542b\u7a7a\u95f4\u5316\u97f3\u9891\u3001\u539f\u59cb\u5b57\u5e55\u3001\u7a7a\u95f4\/\u73af\u5883\u53c2\u6570\u4ee5\u53ca\u7a7a\u95f4\u6d3e\u751f\u5b57\u5e55\u3002<\/p>\n\n\n\n

      \u8bc4\u4ef7\u6307\u6807<\/strong><\/h5>\n\n\n\n
        \n
      1. Codec \u91cd\u5efa\u8d28\u91cf<\/strong>\uff1a\u7528 AuraLoss \u8ba1\u7b97\u539f\u59cb\/\u91cd\u5efa FOA \u7684 STFT \u8ddd\u79bb\u4e0e MEL \u8ddd\u79bb\u3002<\/li>\n\n\n\n
      2. \u751f\u6210\u97f3\u9891\u8d28\u91cf\/\u4e00\u81f4\u6027<\/strong>\uff1a\n
          \n
        • FAD\uff1a\u6bd4\u8f83\u751f\u6210\u4e0e\u771f\u5b9e\u97f3\u9891\u5d4c\u5165\u5206\u5e03\u5dee\u5f02\u3002<\/li>\n\n\n\n
        • KL divergence\uff1a\u7528\u9884\u8bad\u7ec3 ELSA \u8ba1\u7b97\u5206\u5e03\u5dee\u5f02\u3002<\/li>\n\n\n\n
        • CLAP score\uff1a\u7528\u6761\u4ef6\u6587\u672c\u5d4c\u5165\u4e0e\u751f\u6210\u97f3\u9891\u5d4c\u5165\u7684\u4f59\u5f26\u76f8\u4f3c\u5ea6\u3002<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n\n\n\n
          \"\"<\/figure>\n\n\n\n

          \u8868 1 \u5bf9\u6bd4\u4e86\u4e0d\u540c\u538b\u7f29\u7387\u7684 FOA Codec \u5728 Spatial AudioCaps \u6570\u636e\u96c6\u4e0a\u7684\u91cd\u5efa\u8d28\u91cf\u548c\u7a7a\u95f4\u7cbe\u5ea6\u3002<\/p>\n\n\n\n

          \u5f53\u538b\u7f29\u7387\u4ece 32X \u63d0\u5347\u81f3 128X \u65f6\uff0cSTFT Distance \u548c Mel Distance \u53d8\u5316\u8f83\u5c0f\uff0c\u8bf4\u660e\u5373\u4f7f\u5728\u9ad8\u538b\u7f29\u6761\u4ef6\u4e0b\uff0c\u6a21\u578b\u4ecd\u80fd\u8f83\u597d\u5730\u4fdd\u7559\u97f3\u9891\u65f6\u9891\u7ed3\u6784\u3002<\/p>\n\n\n\n

          \u4e0d\u540c\u538b\u7f29\u7387\u6a21\u578b\u5728\u65b9\u4f4d\u89d2\uff08L1 azimuth\uff09\u3001\u4fef\u4ef0\u89d2\uff08L1 elevation\uff09\u548c\u8ddd\u79bb\uff08L1 distance\uff09\u4e0a\u7684\u8bef\u5dee\u57fa\u672c\u4fdd\u6301\u5728\u76f8\u8fd1\u6c34\u5e73\uff0c\u8868\u660e FOA \u7684\u7a7a\u95f4\u7ebf\u7d22\u5728\u9ad8\u538b\u7f29\u6f5c\u7a7a\u95f4\u4e2d\u5e76\u672a\u660e\u663e\u4e22\u5931\u3002<\/p>\n\n\n\n

          \u7efc\u4e0a\uff0c\u5728\u8f83\u9ad8\u538b\u7f29\u6bd4\u4e0b\u8fdb\u884c\u6f5c\u7a7a\u95f4\u6269\u6563\u751f\u6210\u662f\u53ef\u884c\u7684\uff0cFOA Codec \u80fd\u591f\u6709\u6548\u4fdd\u7559\u7a7a\u95f4\u4fe1\u606f\uff0c\u4e3a\u540e\u7eed\u6269\u6563\u6a21\u578b\u63d0\u4f9b\u4e86\u53ef\u9760\u7684\u8f93\u5165\u8868\u793a\u3002<\/p>\n\n\n\n

          \"\"<\/figure>\n\n\n\n

          \u8868 3 \u5bf9\u6bd4\u4e86 \u63cf\u8ff0\u5f0f\uff08Descriptive\uff09<\/strong> \u4e0e \u53c2\u6570\u5f0f\uff08Parametric\uff09<\/strong> ImmerseDiffusion \u6a21\u578b\u5728 Spatial AudioCaps \u6d4b\u8bd5\u96c6\u4e0a\u7684\u751f\u6210\u8d28\u91cf\u4e0e\u7a7a\u95f4\u7cbe\u5ea6\u3002<\/p>\n\n\n\n

          \u63cf\u8ff0\u5f0f\u6a21\u578b\u7684 FAD \u663e\u8457\u4f4e\u4e8e\u53c2\u6570\u5f0f\u6a21\u578b\uff0c\u8bf4\u660e\u5176\u751f\u6210\u97f3\u9891\u5728\u6574\u4f53\u5206\u5e03\u4e0a\u66f4\u63a5\u8fd1\u771f\u5b9e\u6570\u636e\u3002\u4e24\u79cd\u6a21\u578b\u5728 KL \u548c CLAP \u6307\u6807\u4e0a\u8868\u73b0\u63a5\u8fd1\uff0c\u53c2\u6570\u5f0f\u6a21\u578b\u5728 KL \u4e0a\u7565\u4f18\uff0c\u4f46\u5728 CLAP \u4e0a\u7565\u4f4e\u3002<\/p>\n\n\n\n

          \u53c2\u6570\u5f0f\u6a21\u578b\u5728\u65b9\u4f4d\u89d2\u3001\u4fef\u4ef0\u89d2\u548c\u6574\u4f53\u7a7a\u95f4\u89d2\u8bef\u5dee\u4e0a\u660e\u663e\u4f18\u4e8e\u63cf\u8ff0\u5f0f\u6a21\u578b\u3002\u4e24\u79cd\u6a21\u578b\u5728\u8ddd\u79bb\u8bef\u5dee\u4e0a\u7684\u8868\u73b0\u63a5\u8fd1\uff0c\u8bf4\u660e\u8ddd\u79bb\u4f30\u8ba1\u4ecd\u53d7 FOA \u5f3a\u5ea6\u5411\u91cf\u4f30\u8ba1\u8bef\u5dee\u7684\u9650\u5236\uff0c\u5c1a\u672a\u5b8c\u5168\u53d7\u76ca\u4e8e\u53c2\u6570\u5316\u8f93\u5165\u3002<\/p>\n\n\n\n

            \n
          • \u63cf\u8ff0\u5f0f\u6a21\u578b<\/strong>\uff1a\u751f\u6210\u8d28\u91cf\u66f4\u9ad8\uff0c\u9002\u5408\u5f71\u89c6\u3001\u53d9\u4e8b\u7b49\u201c\u8bed\u8a00\u9a71\u52a8\u201d\u7684\u6c89\u6d78\u5f0f\u5185\u5bb9\u521b\u4f5c\uff1b<\/li>\n\n\n\n
          • \u53c2\u6570\u5f0f\u6a21\u578b<\/strong>\uff1a\u7a7a\u95f4\u5b9a\u4f4d\u66f4\u7cbe\u786e\uff0c\u66f4\u9002\u5408\u6e38\u620f\u5f15\u64ce\u3001\u865a\u62df\u4eff\u771f\u7b49\u9700\u8981\u7cbe\u786e\u7a7a\u95f4\u63a7\u5236\u7684\u5e94\u7528\u573a\u666f\u3002<\/li>\n<\/ul>\n\n\n\n

            \u603b\u7ed3<\/h2>\n\n\n\n

            \u672c\u6587\u7684\u65b9\u6cd5\u901a\u8fc7\u5c06\u4e00\u9636 Ambisonics\uff08FOA\uff09\u7a7a\u95f4\u97f3\u9891\u6620\u5c04\u5230\u6f5c\u7a7a\u95f4\uff0c\u5e76\u7ed3\u5408\u57fa\u4e8e Transformer \u7684\u6269\u6563\u6a21\u578b\uff0c\u5b9e\u73b0\u4e86\u5728\u6587\u672c\u3001\u7a7a\u95f4\u3001\u65f6\u95f4\u53ca\u73af\u5883\u6761\u4ef6\u7ea6\u675f\u4e0b\u7684\u4e09\u7ef4\u7a7a\u95f4\u97f3\u9891\u751f\u6210\u3002\u6a21\u578b\u540c\u65f6\u652f\u6301\u63cf\u8ff0\u5f0f\u4e0e\u53c2\u6570\u5f0f\u4e24\u79cd\u63a7\u5236\u65b9\u5f0f\uff0c\u5728\u7075\u6d3b\u6027\u4e0e\u7cbe\u786e\u6027\u4e4b\u95f4\u53d6\u5f97\u4e86\u826f\u597d\u5e73\u8861\u3002\u5b9e\u9a8c\u7ed3\u679c\u8868\u660e\uff0c\u6240\u8bbe\u8ba1\u7684 FOA Codec \u5728\u8f83\u9ad8\u538b\u7f29\u7387\u4e0b\u4ecd\u80fd\u6709\u6548\u4fdd\u7559\u7a7a\u95f4\u4fe1\u606f\uff0c\u4e3a\u6f5c\u7a7a\u95f4\u6269\u6563\u751f\u6210\u63d0\u4f9b\u4e86\u53ef\u9760\u57fa\u7840\uff1b\u5728\u751f\u6210\u9636\u6bb5\uff0c\u63cf\u8ff0\u5f0f\u6a21\u578b\u5728\u6574\u4f53\u97f3\u9891\u8d28\u91cf\u4e0e\u8bed\u4e49\u4e00\u81f4\u6027\u65b9\u9762\u8868\u73b0\u66f4\u4f18\uff0c\u800c\u53c2\u6570\u5f0f\u6a21\u578b\u5728\u7a7a\u95f4\u5b9a\u4f4d\u7cbe\u5ea6\u4e0a\u5177\u6709\u660e\u663e\u4f18\u52bf\uff0c\u9a8c\u8bc1\u4e86\u53cc\u6a21\u5f0f\u8bbe\u8ba1\u5728\u4e0d\u540c\u5e94\u7528\u573a\u666f\u4e0b\u7684\u9002\u7528\u6027\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

            \u4f5c\u8005\uff1aMojtaba Heydari\uff0cMehrez Souden\uff0cBruno Conejo\uff0cJoshua At […]<\/p>\n","protected":false},"author":72,"featured_media":0,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-4768","post","type-post","status-publish","format-standard","hentry","category-events"],"_links":{"self":[{"href":"https:\/\/www.15zhi.net\/blog\/wp-json\/wp\/v2\/posts\/4768","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.15zhi.net\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.15zhi.net\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.15zhi.net\/blog\/wp-json\/wp\/v2\/users\/72"}],"replies":[{"embeddable":true,"href":"https:\/\/www.15zhi.net\/blog\/wp-json\/wp\/v2\/comments?post=4768"}],"version-history":[{"count":1,"href":"https:\/\/www.15zhi.net\/blog\/wp-json\/wp\/v2\/posts\/4768\/revisions"}],"predecessor-version":[{"id":4789,"href":"https:\/\/www.15zhi.net\/blog\/wp-json\/wp\/v2\/posts\/4768\/revisions\/4789"}],"wp:attachment":[{"href":"https:\/\/www.15zhi.net\/blog\/wp-json\/wp\/v2\/media?parent=4768"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.15zhi.net\/blog\/wp-json\/wp\/v2\/categories?post=4768"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.15zhi.net\/blog\/wp-json\/wp\/v2\/tags?post=4768"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}