Difference between revisions of "Asr-language-processing-research-rnng-mn"

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(Time Table)
(Time Table)
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* how to use GPU in rnng
 
* how to use GPU in rnng
 
# learn to use it
 
# learn to use it
||  ||
+
||   
 +
* modify discriminative model,  try to prove the positive function of static memory
 +
# changed train set
 +
# added parameter before cos
 +
# modified model structure
 +
* read the code of Teacher Feng
 +
# understood but did't run
 +
* how to use GPU in rnng
 +
# the result is rnng cannot run fast on GPU
 +
* update the report [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/2/2f/RNNG%2Bmm%E5%AE%9E%E9%AA%8C%E6%8A%A5%E5%91%8A.pdf report]
 +
||
 +
* 90%
 
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|-
 
| 2016/11/14
 
| 2016/11/14
 
|
 
|
* try to implement a dynamic memory  
+
* try to run rnng on multi cpu cores
 +
* refine the models tried before and give the result report
 +
* finish the code of dynamic memory model
 
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Revision as of 08:05, 14 November 2016

Main Idea

People

Yang Feng, Shiyue Zhang, Andi Zhang

Time Table

Date Work Plan Work Done Completion Rate
2016/10/31
  • implement rnng+static memory discriminative model
  1. fix the unexpected action
  2. rerun the original discriminative model
  3. rerun the centred memory rnng model
  4. get wrong instances of original trained model, and get statistics
  5. run the wrong memory rnng model
  6. run the sampled memory rnng model
  7. update experiment report
  • implementation is done, but result is not satisfied.
  1. fixed the unexpected action
  2. reran the original discriminative model
  3. reran the centred memory rnng model
  4. got wrong instances of original trained model, and get statistics
  5. ran the sampled memory rnng model
  6. ran the wrong memory rnng model
  7. updated experiment report [1]
  • 100%
2016/11/7
  • modify discriminative model, try to prove the positive function of static memory
  1. change train set
  2. add parameter before cos
  3. modify model structure
  • read the code of Teacher Feng
  1. understand and run
  • how to use GPU in rnng
  1. learn to use it
  • modify discriminative model, try to prove the positive function of static memory
  1. changed train set
  2. added parameter before cos
  3. modified model structure
  • read the code of Teacher Feng
  1. understood but did't run
  • how to use GPU in rnng
  1. the result is rnng cannot run fast on GPU
  • 90%
2016/11/14
  • try to run rnng on multi cpu cores
  • refine the models tried before and give the result report
  • finish the code of dynamic memory model
2016/11/21
  • modify model
  • try to prove the positive function of dynamic memory
2016/11/28
  • modify model
  • try to prove the positive function of dynamic memory
2016/12/5
  • get the first final rnng+mm discriminative model
2016/12/12
  • give a plan to transfer to generative model
2016/12/19
  • implement rnng+mm generative model
2016/12/26
  • modify model
  • try to prove the positive function of memory

Progress