“2013-10-18”版本间的差异

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Noisy training
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1. With 863 clean test, by adding car & white noise at various levels, obtained significant performance improvement.
 
1. With 863 clean test, by adding car & white noise at various levels, obtained significant performance improvement.
2. The test with both car & white noise benefits from the noisy training.
 
  
 +
2. The test with both car & white noise benefits from the noisy training.
  
 
==Continuous LM ==
 
==Continuous LM ==

2013年10月18日 (五) 01:26的版本

Data sharing

  • LM count files still undelivered!

DNN progress

Sparse DNN

  • Optimal Brain Damage(OBD). Code ready, bug found.

Tencent exps

N/A


Noisy training

1. With 863 clean test, by adding car & white noise at various levels, obtained significant performance improvement.

2. The test with both car & white noise benefits from the noisy training.

Continuous LM

1. Lattice rescoring toolkit is ready. 2. Rescoring is slow with some dense lattices.


QA LM

1. use the QA word segment system 2. train the Q LM & QA ASR system