“Approaches to convert RNNLM to BNLM”版本间的差异

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* VARIATIONAL APPROXIMATION OF LONG-SPAN LANGUAGE MODELS FOR LVCSR[http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5947612&tag=1]
 
* VARIATIONAL APPROXIMATION OF LONG-SPAN LANGUAGE MODELS FOR LVCSR[http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5947612&tag=1]
 
* Conversion of Recurrent Neural Network Language Models to Weighted Finite State Transducers for Automatic Speech Recognition[http://people.irisa.fr/Gwenole.Lecorve/pdf/lecorve12c.pdf]
 
* Conversion of Recurrent Neural Network Language Models to Weighted Finite State Transducers for Automatic Speech Recognition[http://people.irisa.fr/Gwenole.Lecorve/pdf/lecorve12c.pdf]
* Converting Neural Network Language Models into Back-off Language Models for Efficient Decoding in Automatic Speech Recognition[http://delivery.acm.org/10.1145/2590000/2583722/06645438.pdf ip=166.111.134.19&id=2583722&acc=ACTIVE%20SERVICE&key=BF85BBA5741FDC6E%2E587F3204F5B62A59%2E4D4702B0C3E38B35%2E4D4702B0C3E38B35&CFID=593700348&CFTOKEN=42817565&__acm__=1414915690_c0bb48e7020d821b2f5841fa71632ebb]
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* Converting Neural Network Language Models into Back-off Language Models for Efficient Decoding in Automatic Speech Recognition[http://delivery.acm.org/10.1145/2590000/2583722/06645438.pdf?ip=166.111.134.19&id=2583722&acc=ACTIVE%20SERVICE&key=BF85BBA5741FDC6E%2E587F3204F5B62A59%2E4D4702B0C3E38B35%2E4D4702B0C3E38B35&CFID=593700348&CFTOKEN=42817565&__acm__=1414915690_c0bb48e7020d821b2f5841fa71632ebb]
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=related algorithm=
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* gibbs sampling[http://cos.name/2013/01/lda-math-mcmc-and-gibbs-sampling/][http://www.xperseverance.net/blogs/tag/gibbs-sampling/]
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* Kullback–Leibler divergence[http://zh.wikipedia.org/wiki/%E7%9B%B8%E5%AF%B9%E7%86%B5]

2014年11月4日 (二) 14:27的最后版本

main paper

comparing approaches to convert recurrent neural networks into backoff language models for efficient decoding[1]

related paper

  • VARIATIONAL APPROXIMATION OF LONG-SPAN LANGUAGE MODELS FOR LVCSR[2]
  • Conversion of Recurrent Neural Network Language Models to Weighted Finite State Transducers for Automatic Speech Recognition[3]
  • Converting Neural Network Language Models into Back-off Language Models for Efficient Decoding in Automatic Speech Recognition[4]

related algorithm

  • gibbs sampling[5][6]
  • Kullback–Leibler divergence[7]