“2013-10-18”版本间的差异

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QA LM
Continuous LM
第25行: 第25行:
 
==Continuous LM ==
 
==Continuous LM ==
  
1. Lattice rescoring toolkit is ready.
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* Lattice re-scoring toolkit is ready. However the toolkit is very slow for large lattices.
2. Rescoring is slow with some dense lattices.
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* Now checking the code to improve efficiency.
 
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==QA LM==
 
==QA LM==

2013年10月18日 (五) 09:27的版本

Data sharing

  • LM count files still undelivered!

DNN progress

Sparse DNN

  • Optimal Brain Damage(OBD). The initial test shows worse results in weight-cutting experiments compared with simple weight-based cutting.

Tencent exps

N/A


Noisy training

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

  • car noise test


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

Continuous LM

  • Lattice re-scoring toolkit is ready. However the toolkit is very slow for large lattices.
  • Now checking the code to improve efficiency.

QA LM

Just started. Jobs to do:

  1. use the QA-oriented word segment system
  2. train the Q LM with the QA data