“Zhiyong Zhang 2016-04-18”版本间的差异

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*Weekly report
 
*Weekly report
# Character-LM and Word-LM merge
 
:# Union the two can achieve 9.53-wer compared with only word-LM 9.67-wer, but the HCLG is twice bigger than only word-lm;
 
:# Compose get an wer of 64-wer, need deep investigation
 
 
 
# Re-compile nnet3-mpe under the 20160410 kaldi version
 
# Re-compile nnet3-mpe under the 20160410 kaldi version
 
# Assist the restaurant recording of Siason
 
# Assist the restaurant recording of Siason
# Assist the implementation of NG-SGD in nnet1 version with Xiangyu  
+
# Assist the implementation of NG-SGD in nnet1 version with Xiangyu
 +
# Character-LM and Word-LM merge
 +
:# Union the two can achieve 9.53-wer compared with only word-LM 9.67-wer, but the HCLG is twice bigger than only word-lm;
 +
:# Compose get an wer of 64-wer, need deep investigation
  
 
* Next week
 
* Next week
 
# To solve the deletion error in discriminative training  
 
# To solve the deletion error in discriminative training  
 
# To check the SVD re-train failure problem
 
# To check the SVD re-train failure problem

2016年4月18日 (一) 00:53的最后版本

  • Weekly report
  1. Re-compile nnet3-mpe under the 20160410 kaldi version
  2. Assist the restaurant recording of Siason
  3. Assist the implementation of NG-SGD in nnet1 version with Xiangyu
  4. Character-LM and Word-LM merge
  1. Union the two can achieve 9.53-wer compared with only word-LM 9.67-wer, but the HCLG is twice bigger than only word-lm;
  2. Compose get an wer of 64-wer, need deep investigation
  • Next week
  1. To solve the deletion error in discriminative training
  2. To check the SVD re-train failure problem