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• [P1071] Applying Conditional Random Fields On Chinese Syllable Recognition
  Author(s): Li Jie
  
  

  Abstract
  Hidden Markov model (HMM) is successfully used in speech recognition. However, there is an unavoidable flaw in assuming strong independence for sequences labeling in HMM. While Conditional Random Fields (CRFs) can relax this assumption for HMM, and can also solve the label bias problem efficiently. In this paper, we investigate CRFs for Chinese syllable recognition in continuous speech due to its advantages. The experiments show that CRFs can get a good result which is compared to the method of "using phone" for syllable recognition with HMM.

  
   

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