“2013-07-26”版本间的差异

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(以内容“== Data sharing == * LM count files still undelivered! == DNN progress == === Experiments === * Sparse DNN on the ARM board <pre> 1200-1200-1200-3536 ...”创建新页面)
 
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To be done:
 
To be done:
  
1. SuiteSparse lib
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# SuiteSparse lib
2. decrease the hidden layer from 4-2
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# decrease the hidden layer from 4-2
3. Test accuracy on large data set
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# Test accuracy on large data set
  
 
</pre>
 
</pre>
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To DO:
 
To DO:
  
1. Large scale test.
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# Large scale test.
2. CI Phone-based full path confidence estimation.
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# CI Phone-based full path confidence estimation.
  
 
==FST sub-graph integration==
 
==FST sub-graph integration==
  
1. Coding finished.  
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# Coding finished.  
2. Debuging and Test next week.
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# Debuging and Test next week.
  
  
 
== Embedded progress ==
 
== Embedded progress ==
  
1. Graph search costs a lot when the graph is large. Need to improve the indexing performance.
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# Graph search costs a lot when the graph is large. Need to improve the indexing performance.
2. Need to integrate the Kaldi FE with pocket-sphinx decoder.
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# Need to integrate the Kaldi FE with pocket-sphinx decoder.

2013年7月26日 (五) 08:19的版本

Data sharing

  • LM count files still undelivered!

DNN progress

Experiments

  • Sparse DNN on the ARM board
1200-1200-1200-3536                 1200-1200-1200-3536-sparse0.3 (sparsity 1/5)
original atlas:  RT 2.3                         RT 2.3
atlas sparse:    RT 54                          RT 14  
NIST smatmat:    RT 27.3                        RT 5.98
800-800-800-2108                    800-800-800-2108-sparse0.3 (sparsity 2/5):
original atlas: RT 1.3                          RT 1.1
NIST smatmat:   RT 11.9                         RT 5.5

600-600-600-1500 
original atlas: RT 0.9
NIST smatmat:   RT 6.5


To be done:

# SuiteSparse lib
# decrease the hidden layer from 4-2
# Test accuracy on large data set

Tencent exps

GPU & CPU merge

  1. Hold

Confidence estimation

1. DNN-based confidence estimation for decoding and alignment is done. The intuitive testing seems ok.

To DO:

  1. Large scale test.
  2. CI Phone-based full path confidence estimation.

FST sub-graph integration

  1. Coding finished.
  2. Debuging and Test next week.


Embedded progress

  1. Graph search costs a lot when the graph is large. Need to improve the indexing performance.
  2. Need to integrate the Kaldi FE with pocket-sphinx decoder.