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

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(→‎Time Table)
(→‎Time Table)
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| 2016/10/31
 
| 2016/10/31
 
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# implement rnng+static memory discriminative model
+
* implement rnng+static memory discriminative model
−
* fix the unexpected action
+
# fix the unexpected action
−
* rerun the original discriminative model
+
#  rerun the original discriminative model
−
* rerun the centred memory rnng model
+
# rerun the centred memory rnng model
−
* get wrong instances of original trained model, and get statistics
+
#  get wrong instances of original trained model, and get statistics
−
* run the wrong memory rnng model
+
# run the wrong memory rnng model
−
* run the sampled memory rnng model
+
# run the sampled memory rnng model
−
* update experiment report
+
#  update experiment report
 
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−
* fixed the unexpected action
+
* implementation is done, but result is not satisfied.
−
* reran the original discriminative model
+
#  fixed the unexpected action
−
* reran the centred memory rnng model
+
# reran the original discriminative model
−
* got wrong instances of original trained model, and get statistics
+
#  reran the centred memory rnng model
−
* ran the sampled memory rnng model
+
#  got wrong instances of original trained model, and get statistics
−
* ran the wrong memory rnng model
+
# ran the sampled memory rnng model
−
* updated experiment 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]
+
#  ran the wrong memory rnng model
 +
# updated experiment 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]
 
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* 100%
 
* 100%

Revision as of 04:46, 7 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 model
  • try to prove the positive function of static memory
2016/11/14
  • try to implement a dynamic memory
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

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