{"id":741,"date":"2019-07-30T03:22:23","date_gmt":"2019-07-30T03:22:23","guid":{"rendered":"http:\/\/www.yptk.cn\/?p=741"},"modified":"2023-05-01T20:14:29","modified_gmt":"2023-05-01T12:14:29","slug":"%e8%af%ad%e9%9f%b3%e8%af%86%e5%88%ab%e7%9a%84%e6%8a%80%e6%9c%af%e5%8e%9f%e7%90%86%e6%98%af%e4%bb%80%e4%b9%88%ef%bc%9f","status":"publish","type":"post","link":"http:\/\/yptk.cn\/index.php\/2019\/07\/30\/%e8%af%ad%e9%9f%b3%e8%af%86%e5%88%ab%e7%9a%84%e6%8a%80%e6%9c%af%e5%8e%9f%e7%90%86%e6%98%af%e4%bb%80%e4%b9%88%ef%bc%9f\/","title":{"rendered":"\u8bed\u97f3\u8bc6\u522b\u7684\u6280\u672f\u539f\u7406\u662f\u4ec0\u4e48\uff1f"},"content":{"rendered":"

\u8f6c\u81ea\u77e5\u4e4e\uff1a
\n\u7b80\u8981\u7ed9\u5927\u5bb6\u4ecb\u7ecd\u4e00\u4e0b\u8bed\u97f3\u600e\u4e48\u53d8\u6587\u5b57\u7684\u5427\u3002\u9700\u8981\u8bf4\u660e\u7684\u662f\uff0c\u8fd9\u7bc7\u6587\u7ae0\u4e3a\u4e86\u6613\u8bfb\u6027\u800c\u727a\u7272\u4e86\u4e25\u8c28\u6027\uff0c\u56e0\u6b64\u6587\u4e2d\u7684\u5f88\u591a\u8868\u8ff0\u5b9e\u9645\u4e0a\u662f\u4e0d\u51c6\u786e\u7684\u3002\u5bf9\u4e8e\u6709\u5174\u8da3\u6df1\u5165\u4e86\u89e3\u7684\u540c\u5b66\uff0c\u672c\u6587\u7684\u672b\u5c3e\u63a8\u8350\u4e86\u51e0\u4efd\u8fdb\u9636\u9605\u8bfb\u6750\u6599\u3002\u4e0b\u9762\u6211\u4eec\u5f00\u59cb\u3002<\/p>\n

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\n\"c58a25274bcc8788831e6100e9e366fd_hd.jpg\"<\/p>\n

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\n\"554db0c9107727aa1e31a62cca782ada_hd.jpg\"<\/p>\n

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\n\"c5cc0131dc6d38e871953eea0792f7db_hd.jpg\"
\n\u63a5\u4e0b\u6765\u5c31\u8981\u4ecb\u7ecd\u600e\u6837\u628a\u8fd9\u4e2a\u77e9\u9635\u53d8\u6210\u6587\u672c\u4e86\u3002\u9996\u5148\u8981\u4ecb\u7ecd\u4e24\u4e2a\u6982\u5ff5\uff1a<\/p>\n

    \n
  1. \u97f3\u7d20\uff1a\u5355\u8bcd\u7684\u53d1\u97f3\u7531\u97f3\u7d20\u6784\u6210\u3002\u5bf9\u82f1\u8bed\uff0c\u4e00\u79cd\u5e38\u7528\u7684\u97f3\u7d20\u96c6\u662f\u5361\u5185\u57fa\u6885\u9686\u5927\u5b66\u7684\u4e00\u5957\u753139\u4e2a\u97f3\u7d20\u6784\u6210\u7684\u97f3\u7d20\u96c6\uff0c\u53c2\u89c1The CMU Pronouncing Dictionary\u200e\u3002\u6c49\u8bed\u4e00\u822c\u76f4\u63a5\u7528\u5168\u90e8\u58f0\u6bcd\u548c\u97f5\u6bcd\u4f5c\u4e3a\u97f3\u7d20\u96c6\uff0c\u53e6\u5916\u6c49\u8bed\u8bc6\u522b\u8fd8\u5206\u6709\u8c03\u65e0\u8c03\uff0c\u4e0d\u8be6\u8ff0\u3002<\/li>\n
  2. \u72b6\u6001\uff1a\u8fd9\u91cc\u7406\u89e3\u6210\u6bd4\u97f3\u7d20\u66f4\u7ec6\u81f4\u7684\u8bed\u97f3\u5355\u4f4d\u5c31\u884c\u5566\u3002\u901a\u5e38\u628a\u4e00\u4e2a\u97f3\u7d20\u5212\u5206\u62103\u4e2a\u72b6\u6001\u3002<\/li>\n<\/ol>\n

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    \n\u628a\u72b6\u6001\u7ec4\u5408\u6210\u97f3\u7d20\u3002
    \n\u628a\u97f3\u7d20\u7ec4\u5408\u6210\u5355\u8bcd\u3002<\/p>\n

    \u5982\u4e0b\u56fe\u6240\u793a\uff1a
    \n\"beee2a3ce7b1b56de362c9015e5b8ccd_hd.jpg\"<\/p>\n

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    \n

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    \n\"61d5bff9c239e7519e92d98f5bc44689_hd.jpg\"<\/p>\n

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    \u89e3\u51b3\u8fd9\u4e2a\u95ee\u9898\u7684\u5e38\u7528\u65b9\u6cd5\u5c31\u662f\u4f7f\u7528\u9690\u9a6c\u5c14\u53ef\u592b\u6a21\u578b\uff08Hidden Markov Model\uff0cHMM\uff09\u3002\u8fd9\u4e1c\u897f\u542c\u8d77\u6765\u597d\u50cf\u5f88\u9ad8\u6df1\u7684\u6837\u5b50\uff0c\u5b9e\u9645\u4e0a\u7528\u8d77\u6765\u5f88\u7b80\u5355\uff1a
    \n\u7b2c\u4e00\u6b65\uff0c\u6784\u5efa\u4e00\u4e2a\u72b6\u6001\u7f51\u7edc\u3002
    \n\u7b2c\u4e8c\u6b65\uff0c\u4ece\u72b6\u6001\u7f51\u7edc\u4e2d\u5bfb\u627e\u4e0e\u58f0\u97f3\u6700\u5339\u914d\u7684\u8def\u5f84\u3002<\/p>\n

    \u8fd9\u6837\u5c31\u628a\u7ed3\u679c\u9650\u5236\u5728\u9884\u5148\u8bbe\u5b9a\u7684\u7f51\u7edc\u4e2d\uff0c\u907f\u514d\u4e86\u521a\u624d\u8bf4\u5230\u7684\u95ee\u9898\uff0c\u5f53\u7136\u4e5f\u5e26\u6765\u4e00\u4e2a\u5c40\u9650\uff0c\u6bd4\u5982\u4f60\u8bbe\u5b9a\u7684\u7f51\u7edc\u91cc\u53ea\u5305\u542b\u4e86\u201c\u4eca\u5929\u6674\u5929\u201d\u548c\u201c\u4eca\u5929\u4e0b\u96e8\u201d\u4e24\u4e2a\u53e5\u5b50\u7684\u72b6\u6001\u8def\u5f84\uff0c\u90a3\u4e48\u4e0d\u7ba1\u8bf4\u4e9b\u4ec0\u4e48\uff0c\u8bc6\u522b\u51fa\u7684\u7ed3\u679c\u5fc5\u7136\u662f\u8fd9\u4e24\u4e2a\u53e5\u5b50\u4e2d\u7684\u4e00\u53e5\u3002<\/p>\n

    \u90a3\u5982\u679c\u60f3\u8bc6\u522b\u4efb\u610f\u6587\u672c\u5462\uff1f\u628a\u8fd9\u4e2a\u7f51\u7edc\u642d\u5f97\u8db3\u591f\u5927\uff0c\u5305\u542b\u4efb\u610f\u6587\u672c\u7684\u8def\u5f84\u5c31\u53ef\u4ee5\u4e86\u3002\u4f46\u8fd9\u4e2a\u7f51\u7edc\u8d8a\u5927\uff0c\u60f3\u8981\u8fbe\u5230\u6bd4\u8f83\u597d\u7684\u8bc6\u522b\u51c6\u786e\u7387\u5c31\u8d8a\u96be\u3002\u6240\u4ee5\u8981\u6839\u636e\u5b9e\u9645\u4efb\u52a1\u7684\u9700\u6c42\uff0c\u5408\u7406\u9009\u62e9\u7f51\u7edc\u5927\u5c0f\u548c\u7ed3\u6784\u3002<\/p>\n

    \u642d\u5efa\u72b6\u6001\u7f51\u7edc\uff0c\u662f\u7531\u5355\u8bcd\u7ea7\u7f51\u7edc\u5c55\u5f00\u6210\u97f3\u7d20\u7f51\u7edc\uff0c\u518d\u5c55\u5f00\u6210\u72b6\u6001\u7f51\u7edc\u3002\u8bed\u97f3\u8bc6\u522b\u8fc7\u7a0b\u5176\u5b9e\u5c31\u662f\u5728\u72b6\u6001\u7f51\u7edc\u4e2d\u641c\u7d22\u4e00\u6761\u6700\u4f73\u8def\u5f84\uff0c\u8bed\u97f3\u5bf9\u5e94\u8fd9\u6761\u8def\u5f84\u7684\u6982\u7387\u6700\u5927\uff0c\u8fd9\u79f0\u4e4b\u4e3a\u201c\u89e3\u7801\u201d\u3002\u8def\u5f84\u641c\u7d22\u7684\u7b97\u6cd5\u662f\u4e00\u79cd\u52a8\u6001\u89c4\u5212\u526a\u679d\u7684\u7b97\u6cd5\uff0c\u79f0\u4e4b\u4e3aViterbi\u7b97\u6cd5\uff0c\u7528\u4e8e\u5bfb\u627e\u5168\u5c40\u6700\u4f18\u8def\u5f84\u3002<\/p>\n

    \"91e4cb3b716b63d5e18ba710a1a2d770_hd.jpg\"
    \n\u8fd9\u91cc\u6240\u8bf4\u7684\u7d2f\u79ef\u6982\u7387\uff0c\u7531\u4e09\u90e8\u5206\u6784\u6210\uff0c\u5206\u522b\u662f\uff1a<\/p>\n

      \n
    1. \u89c2\u5bdf\u6982\u7387\uff1a\u6bcf\u5e27\u548c\u6bcf\u4e2a\u72b6\u6001\u5bf9\u5e94\u7684\u6982\u7387<\/li>\n
    2. \u8f6c\u79fb\u6982\u7387\uff1a\u6bcf\u4e2a\u72b6\u6001\u8f6c\u79fb\u5230\u81ea\u8eab\u6216\u8f6c\u79fb\u5230\u4e0b\u4e2a\u72b6\u6001\u7684\u6982\u7387<\/li>\n
    3. \u8bed\u8a00\u6982\u7387\uff1a\u6839\u636e\u8bed\u8a00\u7edf\u8ba1\u89c4\u5f8b\u5f97\u5230\u7684\u6982\u7387<\/li>\n<\/ol>\n

      \u5176\u4e2d\uff0c\u524d\u4e24\u79cd\u6982\u7387\u4ece\u58f0\u5b66\u6a21\u578b\u4e2d\u83b7\u53d6\uff0c\u6700\u540e\u4e00\u79cd\u6982\u7387\u4ece\u8bed\u8a00\u6a21\u578b\u4e2d\u83b7\u53d6\u3002\u8bed\u8a00\u6a21\u578b\u662f\u4f7f\u7528\u5927\u91cf\u7684\u6587\u672c\u8bad\u7ec3\u51fa\u6765\u7684\uff0c\u53ef\u4ee5\u5229\u7528\u67d0\u95e8\u8bed\u8a00\u672c\u8eab\u7684\u7edf\u8ba1\u89c4\u5f8b\u6765\u5e2e\u52a9\u63d0\u5347\u8bc6\u522b\u6b63\u786e\u7387\u3002\u8bed\u8a00\u6a21\u578b\u5f88\u91cd\u8981\uff0c\u5982\u679c\u4e0d\u4f7f\u7528\u8bed\u8a00\u6a21\u578b\uff0c\u5f53\u72b6\u6001\u7f51\u7edc\u8f83\u5927\u65f6\uff0c\u8bc6\u522b\u51fa\u7684\u7ed3\u679c\u57fa\u672c\u662f\u4e00\u56e2\u4e71\u9ebb\u3002<\/p>\n

      \u8fd9\u6837\u57fa\u672c\u4e0a\u8bed\u97f3\u8bc6\u522b\u8fc7\u7a0b\u5c31\u5b8c\u6210\u4e86\u3002<\/p>\n

      \u4ee5\u4e0a\u7684\u6587\u5b57\u53ea\u662f\u60f3\u8ba9\u5927\u5bb6\u5bb9\u6613\u7406\u89e3\uff0c\u5e76\u4e0d\u8ffd\u6c42\u4e25\u8c28\u3002\u4e8b\u5b9e\u4e0a\uff0cHMM\u7684\u5185\u6db5\u7edd\u4e0d\u662f\u4e0a\u9762\u6240\u8bf4\u7684\u201c\u65e0\u975e\u662f\u4e2a\u72b6\u6001\u7f51\u7edc\u201d\uff0c\u5982\u679c\u5e0c\u671b\u6df1\u5165\u4e86\u89e3\uff0c\u4e0b\u9762\u7ed9\u51fa\u4e86\u51e0\u7bc7\u9605\u8bfb\u6750\u6599\uff1a<\/p>\n

      1. Rabiner L R. A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE, 1989, 77(2): 257-286.
      \n\u5165\u95e8\u5fc5\u8bfb\u3002\u6df1\u5165\u6d45\u51fa\u5730\u4ecb\u7ecd\u4e86\u57fa\u4e8eHMM\u7684\u8bed\u97f3\u8bc6\u522b\u7684\u539f\u7406\uff0c\u4e0d\u6ce8\u91cd\u516c\u5f0f\u7684\u7ec6\u8282\u63a8\u5bfc\u800c\u662f\u7740\u91cd\u9610\u8ff0\u516c\u5f0f\u80cc\u540e\u7684\u7269\u7406\u610f\u4e49\u3002<\/p>\n

      2. Bilmes J A. A gentle tutorial of the EM algorithm and its application to parameter estimation for Gaussian mixture and hidden Markov models. International Computer Science Institute, 1998, 4(510): 126.
      \n\u8be6\u7ec6\u4ecb\u7ecd\u4e86\u7528E-M\u7b97\u6cd5\u8bad\u7ec3HMM\u53c2\u6570\u7684\u63a8\u5bfc\u8fc7\u7a0b\uff0c\u9996\u5148\u8bb2E-M\u7684\u57fa\u672c\u539f\u7406\uff0c\u7136\u540e\u8bb2\u89e3\u5982\u4f55\u5e94\u7528\u5230GMM\u7684\u8bad\u7ec3\uff0c\u6700\u540e\u8bb2\u89e3\u5982\u4f55\u5e94\u7528\u5230HMM\u7684\u8bad\u7ec3\u3002<\/p>\n

      3. Young S, Evermann G, Gales M, et al. The HTK book (v3.4). Cambridge University, 2006.
      \nHTK Book\uff0c\u5f00\u6e90\u5de5\u5177\u5305HTK\u7684\u6587\u6863\u3002\u867d\u7136\u73b0\u5728HTK\u5df2\u7ecf\u4e0d\u662f\u6700\u6d41\u884c\u7684\u4e86\uff0c\u4f46\u4ecd\u7136\u5f3a\u70c8\u63a8\u8350\u6309\u7167\u4e66\u91cc\u7684\u7b2c\u4e8c\u7ae0\u6d41\u7a0b\u505a\u4e00\u904d\uff0c\u4f60\u53ef\u4ee5\u642d\u5efa\u51fa\u4e00\u4e2a\u7b80\u5355\u7684\u6570\u5b57\u4e32\u8bc6\u522b\u7cfb\u7edf\u3002<\/p>\n

      4. Graves A. Supervised Sequence Labelling with Recurrent Neural Networks. Springer Berlin Heidelberg, 2012: 15-35.
      \n\u57fa\u4e8e\u795e\u7ecf\u7f51\u7edc\u7684\u8bed\u97f3\u8bc6\u522b\u7684\u5165\u95e8\u5fc5\u8bfb\u3002\u4ece\u795e\u7ecf\u7f51\u7edc\u7684\u57fa\u672c\u7ed3\u6784\u3001BP\u7b97\u6cd5\u7b49\u4ecb\u7ecd\u5230 LSTM\u3001CTC\u3002<\/p>\n

      5. \u4fde\u680b, \u9093\u529b. \u89e3\u6790\u6df1\u5ea6\u5b66\u4e60\u2014\u2014\u8bed\u97f3\u8bc6\u522b\u5b9e\u8df5, \u7535\u5b50\u5de5\u4e1a\u51fa\u7248\u793e, 2016.
      \n\u9ad8\u8d28\u91cf\u7684\u4e2d\u6587\u8d44\u6599\u975e\u5e38\u7a00\u6709\uff0c\u63a8\u8350\u4e70\u4e00\u672c\u3002\u6700\u65e9\u628a\u6df1\u5ea6\u5b66\u4e60\u6280\u672f\u5e94\u7528\u4e8e\u8bed\u97f3\u8bc6\u522b\u5c31\u662f\u8fd9\u672c\u4e66\u7684\u4f5c\u8005\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

      \u8f6c\u81ea\u77e5\u4e4e\uff1a \u7b80\u8981\u7ed9\u5927\u5bb6\u4ecb\u7ecd\u4e00\u4e0b\u8bed\u97f3\u600e\u4e48\u53d8\u6587\u5b57\u7684\u5427\u3002\u9700\u8981\u8bf4\u660e\u7684\u662f\uff0c\u8fd9\u7bc7\u6587\u7ae0\u4e3a\u4e86\u6613\u8bfb\u6027\u800c\u727a\u7272\u4e86\u4e25\u8c28\u6027\uff0c\u56e0\u6b64\u6587\u4e2d\u7684\u5f88\u591a\u8868\u8ff0\u5b9e\u9645\u4e0a\u662f\u4e0d\u51c6\u786e\u7684\u3002\u5bf9\u4e8e\u6709\u5174\u8da3\u6df1\u5165\u4e86\u89e3\u7684\u540c\u5b66\uff0c\u672c\u6587\u7684\u672b\u5c3e\u63a8\u8350\u4e86\u51e0\u4efd\u8fdb\u9636\u9605\u8bfb\u6750\u6599\u3002\u4e0b\u9762\u6211\u4eec\u5f00\u59cb\u3002 \u9996\u5148\uff0c\u6211\u4eec\u77e5\u9053\u58f0\u97f3\u5b9e\u9645\u4e0a\u662f\u4e00\u79cd\u6ce2\u3002\u5e38\u89c1\u7684mp3\u7b49\u683c\u5f0f\u90fd\u662f\u538b\u7f29\u683c\u5f0f\uff0c\u5fc5\u987b\u8f6c\u6210\u975e\u538b\u7f29\u7684\u7eaf\u6ce2\u5f62\u6587\u4ef6\u6765\u5904\u7406\uff0c\u6bd4\u5982Windows PCM\u6587\u4ef6\uff0c\u4e5f\u5c31\u662f\u4fd7\u79f0\u7684wav\u6587\u4ef6\u3002wav\u6587\u4ef6\u91cc\u5b58\u50a8\u7684\u9664\u4e86\u4e00\u4e2a\u6587\u4ef6\u5934\u4ee5 […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_crdt_document":"","footnotes":""},"categories":[14],"tags":[],"class_list":["post-741","post","type-post","status-publish","format-standard","hentry","category-wiki"],"_links":{"self":[{"href":"http:\/\/yptk.cn\/index.php\/wp-json\/wp\/v2\/posts\/741","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/yptk.cn\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/yptk.cn\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/yptk.cn\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/yptk.cn\/index.php\/wp-json\/wp\/v2\/comments?post=741"}],"version-history":[{"count":0,"href":"http:\/\/yptk.cn\/index.php\/wp-json\/wp\/v2\/posts\/741\/revisions"}],"wp:attachment":[{"href":"http:\/\/yptk.cn\/index.php\/wp-json\/wp\/v2\/media?parent=741"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/yptk.cn\/index.php\/wp-json\/wp\/v2\/categories?post=741"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/yptk.cn\/index.php\/wp-json\/wp\/v2\/tags?post=741"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}